Surgical visualization and particle trend analysis system

ABSTRACT

A surgical visualization system may include particle trend analysis. The surgical visualization system may include a field programable gate array (FPGA) that is configured to transform sensor information of backscattered laser light into real-time information of particle movement (e.g., blood cells) in a portion of a surgical field. The system may communicate the real-time information to a processor that is remote to the FPGA for aggregation and analysis. The surgical visualization system may display both a metric representing a present state of moving particles and an aggregated state of the moving particles. The system may display both the rate of particle movement and the acceleration for use by the surgeon.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to the following, the contents of each of which are incorporated by reference herein:

U.S. patent application Ser. No. 15/940,663, entitled “Surgical System Distributed Processing,” filed Mar. 29, 2018;

U.S. patent application Ser. No. 15/940,704, entitled “Use Of Laser Light And Red-Green-Blue Coloration To Determine Properties Of Back Scattered Light,” filed Mar. 29, 2018;

U.S. Patent Application, entitled “Method for Operating Tiered Operation Modes in A Surgical System,” filed herewith, with attorney docket number END9287USNP1;

US. Patent Application, entitled “Tiered-Access Surgical Visualization System” filed herewith, with attorney docket number END9287USNP2; and

U.S. Patent Application, entitled “Field Programmable Surgical Visualization System,” filed herewith, with attorney docket number END9287USNP4.

BACKGROUND

Surgical systems often incorporate an imaging system, which can allow the clinician(s) to view the surgical site and/or one or more portions thereof on one or more displays such as a monitor, for example. The display(s) can be local and/or remote to a surgical theater. An imaging system can include a scope with a camera that views the surgical site and transmits the view to a display that is viewable by a clinician. Scopes include, but are not limited to, arthroscopes, angioscopes, bronchoscopes, choledochoscopes, colonoscopes, cytoscopes, duodenoscopes, enteroscopes, esophagogastro-duodenoscopes (gastroscopes), endoscopes, laryngoscopes, nasopharyngo-neproscopes, sigmoidoscopes, thoracoscopes, ureteroscopes, and exoscopes. Imaging systems can be limited by the information that they are able to recognize and/or convey to the clinician(s). For example, certain concealed structures, physical contours, and/or dimensions within a three-dimensional space may be unrecognizable intraoperatively by certain imaging systems. Additionally, certain imaging systems may be incapable of communicating and/or conveying certain information to the clinician(s) intraoperatively.

SUMMARY

A surgical visualization system may include particle trend analysis. The surgical visualization system may include a field programable gate array (FPGA) that is configured to transform sensor information of backscattered laser light into real-time information of particle movement (e.g., blood cells) in a portion of a surgical field. The system may communicate the real-time information to a processor that is remote to the FPGA for aggregation and analysis. The surgical visualization system may display both a metric representing a present state of moving particles and an aggregated state of the moving particles. For example, the system may display both the rate of particle movement and the acceleration for use by the surgeon.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an example computer-implemented interactive surgical system.

FIG. 2 is an example surgical system being used to perform a surgical procedure in an operating room.

FIG. 3 is an example surgical hub paired with a visualization system, a robotic system, and an intelligent instrument.

FIG. 4 illustrates an example surgical data network comprising a modular communication hub configured to connect modular devices located in one or more operating theaters of a healthcare facility, or any room in a healthcare facility specially equipped for surgical operations, to the cloud.

FIG. 5 illustrates an example computer-implemented interactive surgical system.

FIG. 6 illustrates an example surgical hub comprising a plurality of modules coupled to the modular control tower.

FIG. 7 illustrates a logic diagram of an example control system of a surgical instrument or tool.

FIG. 8 illustrates an example surgical instrument or tool comprising a plurality of motors which can be activated to perform various functions.

FIG. 9 illustrates a diagram of an example situationally aware surgical system.

FIG. 10 illustrates a timeline of an illustrative surgical procedure and the inferences that the surgical hub can make from the data detected at each step in the surgical procedure.

FIG. 11 is a block diagram of an example computer-implemented interactive surgical system.

FIG. 12 is a block diagram which illustrates the functional architecture of an example computer-implemented interactive surgical system.

FIG. 13 illustrates a block diagram of an example computer-implemented interactive surgical system that is configured to adaptively generate control program updates for modular devices.

FIG. 14 illustrates an example surgical system that includes a handle having a controller and a motor, an adapter releasably coupled to the handle, and a loading unit releasably coupled to the adapter.

FIGS. 15A and B illustrate an example flow for determining a mode of operation and a example functional block diagram for changing a mode of operation, respectively.

FIGS. 16A-D illustrate an example visualization system.

FIGS. 17A-F illustrate a plurality of laser emitters that may be incorporated in an example visualization system, an illumination of an image sensor having a Bayer pattern of color filters, a graphical representation of the operation of a pixel array for a plurality of frames, a schematic of an example of an operation sequence of chrominance and luminance frames, an example of sensor and emitter patterns, and a graphical representation of the operation of a pixel array, respectively.

FIG. 18 illustrates example instrumentation for NIR spectroscopy.

FIG. 19 illustrates example instrumentation for determining NIRS based on Fourier transform infrared imaging.

FIGS. 20A-C illustrate a change in wavelength of light scattered from moving blood cells.

FIG. 21 illustrates example instrumentation that may be used to detect a Doppler shift in laser light scattered from portions of a tissue.

FIGS. 22 and 23 illustrate example optical effects on light impinging on a tissue having subsurface structures.

FIGS. 24A-D illustrate the detection of moving blood cells at a tissue depth based on a laser Doppler analysis at a variety of laser wavelengths.

FIG. 25 illustrates an example of a use of Doppler imaging to detect the present of subsurface blood vessels.

FIG. 26 illustrates a Doppler shift of blue light due to blood cells flowing through a subsurface blood vessel.

FIG. 27 illustrates example localization of a deep subsurface blood vessel.

FIG. 28 illustrates example localization of a shallow subsurface blood vessel.

FIG. 29 illustrates an example composite image comprising a surface image and an image of a subsurface blood vessel.

FIG. 30 illustrates an example method for determining a depth of a surface feature in a piece of tissue.

FIG. 31A illustrates an example visualization system, and FIG. 31B illustrates an example laser-light sensor with two sensor modules, and FIG. 31C is a graphical representation of an example operation of a pixel array for a plurality of frames.

FIG. 32 illustrates an example method for determining an operating mode.

FIG. 33 illustrates an example method for displaying real-time and trending information to a user.

FIG. 34 depicts an example user interface with real-time and/or trending information being displayed.

FIG. 35 depicts an example upgrade framework.

FIG. 36 illustrates an example method for reconfiguring a field programmable gate array.

DETAILED DESCRIPTION

A surgical hub may have cooperative interactions with one of more means of displaying the image from the laparoscopic scope and information from one of more other smart devices. The Hub may have the capacity of interacting with these multiple displays using an algorithm or control program that enables the combined display and control of the data distributed across the number of displays in communication with the Hub.

Referring to FIG. 1, a computer-implemented interactive surgical system 100 may include one or more surgical systems 102 and a cloud-based system (e.g., the cloud 104 that may include a remote server 113 coupled to a storage device 105). Each surgical system 102 may include at least one surgical hub 106 in communication with the cloud 104 that may include a remote server 113. In one example, as illustrated in FIG. 1, the surgical system 102 includes a visualization system 108, a robotic system 110, and a handheld intelligent surgical instrument 112, which are configured to communicate with one another and/or the hub 106. In some aspects, a surgical system 102 may include an M number of hubs 106, an N number of visualization systems 108, an O number of robotic systems 110, and a P number of handheld intelligent surgical instruments 112, where M, N, O, and P may be integers greater than or equal to one.

In various aspects, the visualization system 108 may include one or more imaging sensors, one or more image-processing units, one or more storage arrays, and one or more displays that are strategically arranged with respect to the sterile field, as illustrated in FIG. 2. In one aspect, the visualization system 108 may include an interface for HL7, PACS, and EMR. Various components of the visualization system 108 are described under the heading “Advanced Imaging Acquisition Module” in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, and in U.S. Patent Application Publication No. US 2019-0200844 A1, titled “METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY,” filed Dec. 4, 2018 the disclosure of both of which is herein incorporated by reference in its entirety.

As illustrated in FIG. 2, a primary display 119 is positioned in the sterile field to be visible to an operator at the operating table 114. In addition, a visualization tower 111 is positioned outside the sterile field. The visualization tower 111 may include a first non-sterile display 107 and a second non-sterile display 109, which face away from each other. The visualization system 108, guided by the hub 106, is configured to utilize the displays 107, 109, and 119 to coordinate information flow to operators inside and outside the sterile field. For example, the hub 106 may cause the visualization system 108 to display a snapshot of a surgical site, as recorded by an imaging device 124, on a non-sterile display 107 or 109, while maintaining a live feed of the surgical site on the primary display 119. The snapshot on the non-sterile display 107 or 109 can permit a non-sterile operator to perform a diagnostic step relevant to the surgical procedure, for example.

In one aspect, the hub 106 may also be configured to route a diagnostic input or feedback entered by a non-sterile operator at the visualization tower 111 to the primary display 119 within the sterile field, where it can be viewed by a sterile operator at the operating table. In one example, the input can be in the form of a modification to the snapshot displayed on the non-sterile display 107 or 109, which can be routed to the primary display 119 by the hub 106.

Referring to FIG. 2, a surgical instrument 112 is being used in the surgical procedure as part of the surgical system 102. The hub 106 may also be configured to coordinate information flow to a display of the surgical instrument 112. For example, in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, and in U.S. Patent Application Publication No. US 2019-0200844 A1, titled “METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY,” filed Dec. 4, 2018, the disclosure of both of which is herein incorporated by reference in its entirety. A diagnostic input or feedback entered by a non-sterile operator at the visualization tower 111 can be routed by the hub 106 to the surgical instrument display 115 within the sterile field, where it can be viewed by the operator of the surgical instrument 112. Example surgical instruments that are suitable for use with the surgical system 102 are described under the heading “Surgical Instrument Hardware” and in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, and in U.S. Patent Application Publication No. US 2019-0200844 A1, titled “METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY,” filed Dec. 4, 2018, the disclosure of both of which is herein incorporated by reference in its entirety, for example.

FIG. 2 depicts an example of a surgical system 102 being used to perform a surgical procedure on a patient who is lying down on an operating table 114 in a surgical operating room 116. A robotic system 110 may be used in the surgical procedure as a part of the surgical system 102. The robotic system 110 may include a surgeon's console 118, a patient side cart 120 (surgical robot), and a surgical robotic hub 122. The patient side cart 120 can manipulate at least one removably coupled surgical tool 117 through a minimally invasive incision in the body of the patient while the surgeon views the surgical site through the surgeon's console 118. An image of the surgical site can be obtained by a medical imaging device 124, which can be manipulated by the patient side cart 120 to orient the imaging device 124. The robotic hub 122 can be used to process the images of the surgical site for subsequent display to the surgeon through the surgeon's console 118.

Other types of robotic systems can be readily adapted for use with the surgical system 102. Various examples of robotic systems and surgical tools that are suitable for use with the present disclosure are described in U.S. Patent Application Publication No. US 2019-0201137 A1 (U.S. patent application Ser. No. 16/209,407), titled METHOD OF ROBOTIC HUB COMMUNICATION, DEFECTION, AND CONTROL, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety.

Various examples of cloud-based analytics that are performed by the cloud 104, and are suitable for use with the present disclosure, are described in U.S. Patent Application Publication No. US 2019-0206569 A1 (U.S. patent application Ser. No. 16/209,403), titled METHOD OF CLOUD BASED DATA ANALYTICS FOR USE WITH THE HUB, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety.

In various aspects, the imaging device 124 may include at least one image sensor and one or more optical components. Suitable image sensors may include, but are not limited to, Charge-Coupled Device (CCD) sensors and Complementary Metal-Oxide Semiconductor (CMOS) sensors.

The optical components of the imaging device 124 may include one or more illumination sources and/or one or more lenses. The one or more illumination sources may be directed to illuminate portions of the surgical field. The one or more image sensors may receive light reflected or refracted from the surgical field, including light reflected or refracted from tissue and/or surgical instruments.

The one or more illumination sources may be configured to radiate electromagnetic energy in the visible spectrum as well as the invisible spectrum. The visible spectrum, sometimes referred to as the optical spectrum or luminous spectrum, is that portion of the electromagnetic spectrum that is visible to (i.e., can be detected by) the human eye and may be referred to as visible light or simply light. A typical human eye will respond to wavelengths in air that are from about 380 nm to about 750 nm.

The invisible spectrum (e.g., the non-luminous spectrum) is that portion of the electromagnetic spectrum that lies below and above the visible spectrum (i.e., wavelengths below about 380 nm and above about 750 nm). The invisible spectrum is not detectable by the human eye. Wavelengths greater than about 750 nm are longer than the red visible spectrum, and they become invisible infrared (IR), microwave, and radio electromagnetic radiation. Wavelengths less than about 380 nm are shorter than the violet spectrum, and they become invisible ultraviolet, x-ray, and gamma ray electromagnetic radiation.

In various aspects, the imaging device 124 is configured for use in a minimally invasive procedure. Examples of imaging devices suitable for use with the present disclosure include, but not limited to, an arthroscope, angioscope, bronchoscope, choledochoscope, colonoscope, cytoscope, duodenoscope, enteroscope, esophagogastro-duodenoscope (gastroscope), endoscope, laryngoscope, nasopharvngo-neproscope, sigmoidoscope, thoracoscope, and ureteroscope.

The imaging device may employ multi-spectrum monitoring to discriminate topography and underlying structures. A multi-spectral image is one that captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or by the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, e.g., IR and ultraviolet. Spectral imaging can allow extraction of additional information the human eye fails to capture with its receptors for red, green, and blue. The use of multi-spectral imaging is described in greater detail under the heading “Advanced Imaging Acquisition Module” in U.S. Patent Application Publication No. US 2019-0200844 A1 (U.S. patent application Ser. No. 16/209,385), titled METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY, filed Dec. 4, 2018, the disclosure of which is herein incorporated by reference in its entirety. Multi-spectrum monitoring can be a useful tool in relocating a surgical field after a surgical task is completed to perform one or more of the previously described tests on the treated tissue. It is axiomatic that strict sterilization of the operating room and surgical equipment is required during any surgery. The strict hygiene and sterilization conditions required in a “surgical theater,” i.e., an operating or treatment room, necessitate the highest possible sterility of all medical devices and equipment. Part of that sterilization process is the need to sterilize anything that comes in contact with the patient or penetrates the sterile field, including the imaging device 124 and its attachments and components. It will be appreciated that the sterile field may be considered a specified area, such as within a tray or on a sterile towel, that is considered free of microorganisms, or the sterile field may be considered an area, immediately around a patient, who has been prepared for a surgical procedure. The sterile field may include the scrubbed team members, who are properly attired, and all furniture and fixtures in the area.

Referring now to FIG. 3, a hub 106 is depicted in communication with a visualization system 108, a robotic system 110, and a handheld intelligent surgical instrument 112. The hub 106 includes a hub display 135, an imaging module 138, a generator module 140, a communication module 130, a processor module 132, a storage array 134, and an operating-room mapping module 133. In certain aspects, as illustrated in FIG. 3, the hub 106 further includes a smoke evacuation module 126 and/or a suction/irrigation module 128. During a surgical procedure, energy application to tissue, for sealing and/or cutting, is generally associated with smoke evacuation, suction of excess fluid, and/or irrigation of the tissue. Fluid, power, and/or data lines from different sources are often entangled during the surgical procedure. Valuable time can be lost addressing this issue during a surgical procedure. Detangling the lines may necessitate disconnecting the lines from their respective modules, which may require resetting the modules. The hub modular enclosure 136 offers a unified environment for managing the power, data, and fluid lines, which reduces the frequency of entanglement between such lines. Aspects of the present disclosure present a surgical hub for use in a surgical procedure that involves energy application to tissue at a surgical site. The surgical hub includes a hub enclosure and a combo generator module slidably receivable in a docking station of the hub enclosure. The docking station includes data and power contacts. The combo generator module includes two or more of an ultrasonic energy generator component, a bipolar RF energy generator component, and a monopolar RF energy generator component that are housed in a single unit. In one aspect, the combo generator module also includes a smoke evacuation component, at least one energy delivery cable for connecting the combo generator module to a surgical instrument, at least one smoke evacuation component configured to evacuate smoke, fluid, and/or particulates generated by the application of therapeutic energy to the tissue, and a fluid line extending from the remote surgical site to the smoke evacuation component. In one aspect, the fluid line is a first fluid line and a second fluid line extends from the remote surgical site to a suction and irrigation module slidably received in the hub enclosure. In one aspect, the hub enclosure comprises a fluid interface. Certain surgical procedures may require the application of more than one energy type to the tissue. One energy type may be more beneficial for cutting the tissue, while another different energy type may be more beneficial for sealing the tissue. For example, a bipolar generator can be used to seal the tissue while an ultrasonic generator can be used to cut the sealed tissue. Aspects of the present disclosure present a solution where a hub modular enclosure 136 is configured to accommodate different generators, and facilitate an interactive communication therebetween. One of the advantages of the hub modular enclosure 136 is enabling the quick removal and/or replacement of various modules. Aspects of the present disclosure present a modular surgical enclosure for use in a surgical procedure that involves energy application to tissue. The modular surgical enclosure includes a first energy-generator module, configured to generate a first energy for application to the tissue, and a first docking station comprising a first docking port that includes first data and power contacts, wherein the first energy-generator module is slidably movable into an electrical engagement with the power and data contacts and wherein the first energy-generator module is slidably movable out of the electrical engagement with the first power and data contacts. Further to the above, the modular surgical enclosure also includes a second energy-generator module configured to generate a second energy, different than the first energy, for application to the tissue, and a second docking station comprising a second docking port that includes second data and power contacts, wherein the second energy-generator module is slidably movable into an electrical engagement with the power and data contacts, and wherein the second energy-generator module is slidably movable out of the electrical engagement with the second power and data contacts. In addition, the modular surgical enclosure also includes a communication bus between the first docking port and the second docking port, configured to facilitate communication between the first energy-generator module and the second energy-generator module. Referring to FIG. 3, aspects of the present disclosure are presented for a hub modular enclosure 136 that allows the modular integration of a generator module 140, a smoke evacuation module 126, and a suction/irrigation module 128. The hub modular enclosure 136 further facilitates interactive communication between the modules 140, 126, 128. The generator module 140 can be a generator module with integrated monopolar, bipolar, and ultrasonic components supported in a single housing unit slidably insertable into the hub modular enclosure 136. The generator module 140 can be configured to connect to a monopolar device 142, a bipolar device 144, and an ultrasonic device 146. Alternatively, the generator module 140 may comprise a series of monopolar, bipolar, and/or ultrasonic generator modules that interact through the hub modular enclosure 136. The hub modular enclosure 136 can be configured to facilitate the insertion of multiple generators and interactive communication between the generators docked into the hub modular enclosure 136 so that the generators would act as a single generator.

FIG. 4 illustrates a surgical data network 201 comprising a modular communication hub 203 configured to connect modular devices located in one or more operating theaters of a healthcare facility, or any room in a healthcare facility specially equipped for surgical operations, to a cloud-based system (e.g., the cloud 204 that may include a remote server 213 coupled to a storage device 205). In one aspect, the modular communication hub 203 comprises a network hub 207 and/or a network switch 209 in communication with a network router. The modular communication hub 203 also can be coupled to a local computer system 210 to provide local computer processing and data manipulation. The surgical data network 201 may be configured as passive, intelligent, or switching. A passive surgical data network serves as a conduit for the data, enabling it to go from one device (or segment) to another and to the cloud computing resources. An intelligent surgical data network includes additional features to enable the traffic passing through the surgical data network to be monitored and to configure each port in the network hub 207 or network switch 209. An intelligent surgical data network may be referred to as a manageable hub or switch. A switching hub reads the destination address of each packet and then forwards the packet to the correct port.

Modular devices 1 a-1 n located in the operating theater may be coupled to the modular communication hub 203. The network hub 207 and/or the net-work switch 209 may be coupled to a network router 211 to connect the devices 1 a-1 n to the cloud 204 or the local computer system 210. Data associated with the devices 1 a-1 n may be transferred to cloud-based computers via the router for remote data processing and manipulation. Data associated with the devices 1 a-1 n may also be transferred to the local computer system 210 for local data processing and manipulation. Modular devices 2 a-2 m located in the same operating theater also may be coupled to a network switch 209. The network switch 209 may be coupled to the network hub 207 and/or the network router 211 to connect to the devices 2 a-2 m to the cloud 204. Data associated with the devices 2 a-2 n may be transferred to the cloud 204 via the network router 211 for data processing and manipulation. Data associated with the devices 2 a-2 m may also be transferred to the local computer system 210 for local data processing and manipulation.

It will be appreciated that the surgical data network 201 may be expanded by interconnecting multiple network hubs 207 and/or multiple network switches 209 with multiple network routers 211. The modular communication hub 203 may be contained in a modular control tower configured to receive multiple devices 1 a-1 n/2 a-2 m. The local computer system 210 also may be contained in a modular control tower. The modular communication hub 203 is connected to a display 212 to display images obtained by some of the devices 1 a-In/2 a-2 m, for example during surgical procedures. In various aspects, the devices 1 a-1 n/2 a-2 m may include, for example, various modules such as an imaging module 138 coupled to an endoscope, a generator module 140 coupled to an energy-based surgical device, a smoke evacuation module 126, a suction/irrigation module 128, a communication module 130, a processor module 132, a storage array 134, a surgical device coupled to a display, and/or a non-contact sensor module, among other modular devices that may be connected to the modular communication hub 203 of the surgical data network 201.

In one aspect, the surgical data network 201 may comprise a combination of network hub(s), network switch(es), and network router(s) connecting the devices 1 a-1 n/2 a-2 m to the cloud. Any one of or all of the devices 1 a-In/2 a-2 m coupled to the network hub or network switch may collect data in real time and transfer the data to cloud computers for data processing and manipulation. It will be appreciated that cloud computing relies on sharing computing resources rather than having local servers or personal devices to handle software applications. The word “cloud” may be used as a metaphor for “the Internet,” although the term is not limited as such. Accordingly, the term “cloud computing” may be used herein to refer to “a type of Internet-based computing,” where different services-such as servers, storage, and applications—are delivered to the modular communication hub 203 and/or computer system 210 located in the surgical theater (e.g., a fixed, mobile, temporary, or field operating room or space) and to devices connected to the modular communication hub 203 and/or computer system 210 through the Internet. The cloud infrastructure may be maintained by a cloud service provider. In this context, the cloud service provider may be the entity that coordinates the usage and control of the devices 1 a-1 n/2 a-2 m located in one or more operating theaters. The cloud computing services can perform a large number of calculations based on the data gathered by smart surgical instruments, robots, and other computerized devices located in the operating theater. The hub hardware enables multiple devices or connections to be connected to a computer that communicates with the cloud computing resources and storage.

Applying cloud computer data processing techniques on the data collected by the devices 1 a-1 n/2 a-2 m, the surgical data network can provide improved surgical outcomes, reduced costs, and improved patient satisfaction. At least some of the devices 1 a-1 n/2 a-2 m may be employed to view tissue states to assess leaks or perfusion of sealed tissue after a tissue sealing and cutting procedure. At least some of the devices 1 a-1 n/2 a-2 m may be employed to identify pathology, such as the effects of diseases, using the cloud-based computing to examine data including images of samples of body tissue for diagnostic purposes. This may include localization and margin confirmation of tissue and phenotypes. At least some of the devices 1 a-1 n/2 a-2 m may be employed to identify anatomical structures of the body using a variety of sensors integrated with imaging devices and techniques such as overlaying images captured by multiple imaging devices. The data gathered by the devices 1 a-1 n/2 a-2 m, including image data, may be transferred to the cloud 204 or the local computer system 210 or both for data processing and manipulation including image processing and manipulation. The data may be analyzed to improve surgical procedure outcomes by determining if further treatment, such as the application of endoscopic intervention, emerging technologies, a targeted radiation, targeted intervention, and precise robotics to tissue-specific sites and conditions, may be pursued. Such data analysis may further employ outcome analytics processing, and using standardized approaches may provide beneficial feedback to either confirm surgical treatments and the behavior of the surgeon or suggest modifications to surgical treatments and the behavior of the surgeon.

The operating theater devices 1 a-1 n may be connected to the modular communication hub 203 over a wired channel or a wireless channel depending on the configuration of the devices 1 a-1 n to a network hub. The network hub 207 may be implemented, in one aspect, as a local network broadcast device that works on the physical layer of the Open System Interconnection (OSI) model. The network hub may provide connectivity to the devices 1 a-1 n located in the same operating theater network. The network hub 207 may collect data in the form of packets and sends them to the router in half duplex mode. The network hub 207 may not store any media access control/Internet Protocol (MAC/IP) to transfer the device data. Only one of the devices 1 a-1 n can send data at a time through the network hub 207. The network hub 207 may not have routing tables or intelligence regarding where to send information and broadcasts all network data across each connection and to a remote server 213 (FIG. 4) over the cloud 204. The network hub 207 can detect basic network errors such as collisions, but having all information broadcast to multiple ports can be a security risk and cause bottlenecks.

The operating theater devices 2 a-2 m may be connected to a network switch 209 over a wired channel or a wireless channel. The network switch 209 works in the data link layer of the OSI model. The network switch 209 may be a multicast device for connecting the devices 2 a-2 m located in the same operating theater to the network. The network switch 209 may send data in the form of frames to the network router 211 and works in full duplex mode. Multiple devices 2 a-2 m can send data at the same time through the network switch 209. The network switch 209 stores and uses MAC addresses of the devices 2 a-2 m to transfer data.

The network hub 207 and/or the network switch 209 may be coupled to the network router 211 for connection to the cloud 204. The network router 211 works in the network layer of the OSI model. The network router 211 creates a route for transmitting data packets received from the network hub 207 and/or network switch 211 to cloud-based computer resources for further processing and manipulation of the data collected by any one of or all the devices 1 a-1 n/2 a-2 m. The network router 211 may be employed to connect two or more different networks located in different locations, such as, for example, different operating theaters of the same healthcare facility or different networks located in different operating theaters of different healthcare facilities. The network router 211 may send data in the form of packets to the cloud 204 and works in full duplex mode. Multiple devices can send data at the same time. The network router 211 uses IP addresses to transfer data.

In an example, the network hub 207 may be implemented as a USB hub, which allows multiple USB devices to be connected to a host computer. The USB hub may expand a single USB port into several tiers so that there are more ports available to connect devices to the host system computer. The network hub 207 may include wired or wireless capabilities to receive information over a wired channel or a wireless channel. In one aspect, a wireless USB short-range, high-bandwidth wireless radio communication protocol may be employed for communication between the devices 1 a-1 n and devices 2 a-2 m located in the operating theater.

In examples, the operating theater devices 1 a-1 n/2 a-2 m may communicate to the modular communication hub 203 via Bluetooth wireless technology standard for exchanging data over short distances (using short-wavelength UHF radio waves in the ISM band from 2.4 to 2.485 GHz) from fixed and mobile devices and building personal area networks (PANs). The the operating theater devices 1 a-1 n/2 a-2 m may communicate to the modular communication hub 203 via a number of wireless or wired communication standards or protocols, including but not limited to Wi-Fi (IEEE 802.11 family), WiMAX (IEEE 802.16 family), IEEE 802.20, new radio (NR), long-term evolution (LTE), and Ev-DO, HSPA+, IISDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, DECT, and Ethernet derivatives thereof, as well as any other wireless and wired protocols that are designated as 3G, 4G, 5G, and beyond. The computing module may include a plurality of communication modules. For instance, a first communication module may be dedicated to shorter-range wireless communications such as Wi-Fi and Bluetooth, and a second communication module may be dedicated to longer-range wireless communications such as GPS, EDGE, GPRS, CDMA, WiMAX, LTE, Ev-DO, and others.

The modular communication hub 203 may serve as a central connection for one or all of the operating theater devices 1 a-1 n/2 a-2 m and may handle a data type known as frames. Frames may carry the data generated by the devices 1 a-1 n/2 a-2 m. When a frame is received by the modular communication hub 203, it is amplified and transmitted to the network router 211, which transfers the data to the cloud computing resources by using a number of wireless or wired communication standards or protocols, as described herein.

The modular communication hub 203 can be used as a standalone device or be connected to compatible network hubs and network switches to form a larger network. The modular communication hub 203 can be generally easy to install, configure, and maintain, making it a good option for networking the operating theater devices 1 a-1 n/2 a-2 m.

FIG. 5 illustrates a computer-implemented interactive surgical system 200. The computer-implemented interactive surgical system 200 is similar in many respects to the computer-implemented interactive surgical system 100. For example, the computer-implemented interactive surgical system 200 includes one or more surgical systems 202, which are similar in many respects to the surgical systems 102. Each surgical system 202 includes at least one surgical hub 206 in communication with a cloud 204 that may include a remote server 213. In one aspect, the computer-implemented interactive surgical system 200 comprises a modular control tower 236 connected to multiple operating theater devices such as, for example, intelligent surgical instruments, robots, and other computerized devices located in the operating theater. As shown in FIG. 6, the modular control tower 236 comprises a modular communication hub 203 coupled to a computer system 210.

As illustrated in the example of FIG. 5, the modular control tower 236 may be coupled to an imaging module 238 that may be coupled to an endoscope 239, a generator module 240 that may be coupled to an energy device 241, a smoke evacuator module 226, a suction/irrigation module 228, a communication module 230, a processor module 232, a storage array 234, a smart device/instrument 235 optionally coupled to a display 237, and a non-contact sensor module 242. The operating theater devices may be coupled to cloud computing resources and data storage via the modular control tower 236. A robot hub 222 also may be connected to the modular control tower 236 and to the cloud computing resources. The devices/instruments 235, visualization systems 208, among others, may be coupled to the modular control tower 236 via wired or wireless communication standards or protocols, as described herein. The modular control tower 236 may be coupled to a hub display 215 (e.g., monitor, screen) to display and overlay images received from the imaging module, device/instrument display, and/or other visualization systems 208. The hub display also may display data received from devices connected to the modular control tower in conjunction with images and overlaid images.

FIG. 6 illustrates a surgical hub 206 comprising a plurality of modules coupled to the modular control tower 236. The modular control tower 236 may comprise a modular communication hub 203, e.g., a network connectivity device, and a computer system 210 to provide local processing, visualization, and imaging, for example. As shown in FIG. 6, the modular communication hub 203 may be connected in a tiered configuration to expand the number of modules (e.g., devices) that may be connected to the modular communication hub 203 and transfer data associated with the modules to the computer system 210, cloud computing resources, or both. As shown in FIG. 6, each of the network hubs/switches in the modular communication hub 203 may include three downstream ports and one upstream port. The upstream network hub/switch may be connected to a processor to provide a communication connection to the cloud computing resources and a local display 217. Communication to the cloud 204 may be made either through a wired or a wireless communication channel.

The surgical hub 206 may employ a non-contact sensor module 242 to measure the dimensions of the operating theater and generate a map of the surgical theater using either ultrasonic or laser-type non-contact measurement devices. An ultrasound-based non-contact sensor module may scan the operating theater by transmitting a burst of ultrasound and receiving the echo when it bounces off the perimeter walls of an operating theater as described under the heading “Surgical Hub Spatial Awareness Within an Operating Room” in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, U.S. Patent Application Publication No. US 2019-0200844 A1, titled “METHOD OF HUB COMMUNICATION, PROCESSING, STORAGE AND DISPLAY,” filed Dec. 4, 2018, the disclosure of both of which is herein incorporated by reference in its entirety, in which the sensor module is configured to determine the size of the operating theater and to adjust Bluetooth-pairing distance limits. A laser-based non-contact sensor module may scan the operating theater by transmitting laser light pulses, receiving laser light pulses that bounce off the perimeter walls of the operating theater, and comparing the phase of the transmitted pulse to the received pulse to determine the size of the operating theater and to adjust Bluetooth pairing distance limits, for example.

The computer system 210 may comprise a processor 244 and a network interface 245. The processor 244 can be coupled to a communication module 247, storage 248, memory 249, non-volatile memory 250, and input/output interface 251 via a system bus. The system bus can be any of several types of bus structure(s) including the memory bus or memory controller, a peripheral bus or external bus, and/or a local bus using any variety of available bus architectures including, but not limited to, 9-bit bus, Industrial Standard Architecture (ISA), Micro-Charmel Architecture (MSA), Extended ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect (PCI), USB, Advanced Graphics Port (AGP), Personal Computer Memory Card International Association bus (PCMCIA), Small Computer Systems Interface (SCSI), or any other proprietary bus.

The processor 244 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In one aspect, the processor may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle serial random access memory (SRAM), an internal read-only memory (ROM) loaded with StellarisWare® software, a 2 KB electrically erasable programmable read-only memory (EEPROM), and/or one or more pulse width modulation (PWM) modules, one or more quadrature encoder inputs (QEI) analogs, one or more 12-bit analog-to-digital converters (ADCs) with 12 analog input channels, details of which are available for the product datasheet.

In one aspect, the processor 244 may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x, known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.

The system memory may include volatile memory and non-volatile memory. The basic input/output system (BIOS), containing the basic routines to transfer information between elements within the computer system, such as during start-up, is stored in non-volatile memory. For example, the non-volatile memory can include ROM, programmable ROM (PROM), electrically programmable ROM (EPROM), EEPROM, or flash memory. Volatile memory includes random-access memory (RAM), which acts as external cache memory. Moreover, RAM is available in many forms such as SRAM, dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).

The computer system 210 also may include removable/non-removable, volatile/non-volatile computer storage media, such as for example disk storage. The disk storage can include, but is not limited to, devices like a magnetic disk drive, floppy disk drive, tape drive, Jaz drive, Zip drive, LS-60) drive, flash memory card, or memory stick. In addition, the disk storage can include storage media separately or in combination with other storage media including, but not limited to, an optical disc drive such as a compact disc ROM device (CD-ROM), compact disc recordable drive (CD-R Drive), compact disc rewritable drive (CD-RW Drive), or a digital versatile disc ROM drive (DVD-ROM). To facilitate the connection of the disk storage devices to the system bus, a removable or non-removable interface may be employed.

It is to be appreciated that the computer system 210 may include software that acts as an intermediary between users and the basic computer resources described in a suitable operating environment. Such software may include an operating system. The operating system, which can be stored on the disk storage, may act to control and allocate resources of the computer system. System applications may take advantage of the management of resources by the operating system through program modules and program data stored either in the system memory or on the disk storage. It is to be appreciated that various components described herein can be implemented with various operating systems or combinations of operating systems.

A user may enter commands or information into the computer system 210 through input device(s) coupled to the I/O interface 251. The input devices may include, but are not limited to, a pointing device such as a mouse, trackball, stylus, touch pad, keyboard, microphone, joystick, game pad, satellite dish, scanner, TV tuner card, digital camera, digital video camera, web camera, and the like. These and other input devices connect to the processor through the system bus via interface port(s). The interface port(s) include, for example, a serial port, a parallel port, a game port, and a USB. The output device(s) use some of the same types of ports as input device(s). Thus, for example, a USB port may be used to provide input to the computer system and to output information from the computer system to an output device. An output adapter may be provided to illustrate that there can be some output devices like monitors, displays, speakers, and printers, among other output devices that may require special adapters. The output adapters may include, by way of illustration and not limitation, video and sound cards that provide a means of connection between the output device and the system bus. It should be noted that other devices and/or systems of devices, such as remote computer(s), may provide both input and output capabilities.

The computer system 210 can operate in a networked environment using logical connections to one or more remote computers, such as cloud computer(s), or local computers. The remote cloud computer(s) can be a personal computer, server, router, network PC, workstation, microprocessor-based appliance, peer device, or other common network node, and the like, and typically includes many or all of the elements described relative to the computer system. For purposes of brevity, only a memory storage device is illustrated with the remote computer(s). The remote computer(s) may be logically connected to the computer system through a network interface and then physically connected via a communication connection. The network interface may encompass communication networks such as local area networks (LANs) and wide area networks (WANs). LAN technologies may include Fiber Distributed Data Interface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet/IEEE 802.3, Token Ring/IEEE 802.5 and the like. WAN technologies may include, but are not limited to, point-to-point links, circuit-switching networks like Integrated Services Digital Networks (ISDN) and variations thereon, packet-switching networks, and Digital Subscriber Lines (DSL).

In various aspects, the computer system 210 of FIG. 6, the imaging module 238 and/or visualization system 208, and/or the processor module 232 of FIGS. 5-6, may comprise an image processor, image-processing engine, media processor, or any specialized digital signal processor (DSP) used for the processing of digital images. The image processor may employ parallel computing with single instruction, multiple data (SIMD) or multiple instruction, multiple data (IMID) technologies to increase speed and efficiency. The digital image-processing engine can perform a range of tasks. The image processor may be a system on a chip with multicore processor architecture.

The communication connection(s) may refer to the hardware/software employed to connect the network interface to the bus. While the communication connection is shown for illustrative clarity inside the computer system, it can also be external to the computer system 210. The hardware/software necessary for connection to the network interface may include, for illustrative purposes only, internal and external technologies such as modems, including regular telephone-grade modems, cable modems, and DSL modems, ISDN adapters, and Ethernet cards.

FIG. 7 illustrates a logic diagram of a control system 470 of a surgical instrument or tool in accordance with one or more aspects of the present disclosure. The system 470 may comprise a control circuit. The control circuit may include a microcontroller 461 comprising a processor 462 and a memory 468. One or more of sensors 472, 474, 476, for example, provide real-time feedback to the processor 462. A motor 482, driven by a motor driver 492, operably couples a longitudinally movable displacement member to drive the I-beam knife element. A tracking system 480 may be configured to determine the position of the longitudinally movable displacement member. The position information may be provided to the processor 462, which can be programmed or configured to determine the position of the longitudinally movable drive member as well as the position of a firing member, firing bar, and I-beam knife element. Additional motors may be provided at the tool driver interface to control I-beam firing, closure tube travel, shaft rotation, and articulation. A display 473 may display a variety of operating conditions of the instruments and may include touch screen functionality for data input. Information displayed on the display 473 may be overlaid with images acquired via endoscopic imaging modules.

In one aspect, the microcontroller 461 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas instruments. In one aspect, the main microcontroller 461 may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle SRAM, and internal ROM loaded with StellarisWare®? software, a 2 KB EEPROM, one or more PWM modules, one or more QEI analogs, and/or one or more 12-bit ADCs with 12 analog input channels, details of which are available for the product datasheet.

In one aspect, the microcontroller 461 may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x, known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.

The microcontroller 461 may be programmed to perform various functions such as precise control over the speed and position of the knife and articulation systems. In one aspect, the microcontroller 461 may include a processor 462 and a memory 468. The electric motor 482 may be a brushed direct current (DC) motor with a gearbox and mechanical links to an articulation or knife system. In one aspect, a motor driver 492 may be an A3941 available from Allegro Microsystems, Inc. Other motor drivers may be readily substituted for use in the tracking system 480 comprising an absolute positioning system. A detailed description of an absolute positioning system is described in U.S. Patent Application Publication No. 2017/0296213, titled SYSTEMS AND METHODS FOR CONTROLLING A SURGICAL STAPLING AND CUTTING INSTRUMENT, which published on Oct. 19, 2017, which is herein incorporated by reference in its entirety. The microcontroller 461 may be programmed to provide precise control over the speed and position of displacement members and articulation systems. The microcontroller 461 may be configured to compute a response in the software of the microcontroller 461. The computed response may be compared to a measured response of the actual system to obtain an “observed” response, which is used for actual feedback decisions. The observed response may be a favorable, tuned value that balances the smooth, continuous nature of the simulated response with the measured response, which can detect outside influences on the system.

In some examples, the motor 482 may be controlled by the motor driver 492 and can be employed by the firing system of the surgical instrument or tool. In various forms, the motor 482 may be a brushed DC driving motor having a maximum rotational speed of approximately 25,000 RPM. In some examples, the motor 482 may include a brushless motor, a cordless motor, a synchronous motor, a stepper motor, or any other suitable electric motor. The motor driver 492 may comprise an H-bridge driver comprising field-effect transistors (FETs), for example. The motor 482 can be powered by a power assembly releasably mounted to the handle assembly or tool housing for supplying control power to the surgical instrument or tool. The power assembly may comprise a battery which may include a number of battery cells connected in series that can be used as the power source to power the surgical instrument or tool. In certain circumstances, the battery cells of the power assembly may be replaceable and/or rechargeable. In at least one example, the battery cells can be lithium-ion batteries which can be couplable to and separable from the power assembly.

The motor driver 492 may be an A3941 available from Allegro Microsystems, Inc. The A3941 492 may be a full-bridge controller for use with external N-channel power metal-oxide semiconductor field-effect transistors (MOSFETs) specifically designed for inductive loads, such as brush DC motors. The driver 492 may comprise a unique charge pump regulator that can provide full (>10 V) gate drive for battery voltages down to 7 V and can allow the A3941 to operate with a reduced gate drive, down to 5.5 V. A bootstrap capacitor may be employed to provide the above battery supply voltage required for N-channel MOSFETs. An internal charge pump for the high-side drive may allow DC (100% duty cycle) operation. The full bridge can be driven in fast or slow decay modes using diode or synchronous rectification. In the slow decay mode, current recirculation can be through the high-side or the lowside FETs. The power FETs may be protected from shoot-through by resistor-adjustable dead time. Integrated diagnostics provide indications of undervoltage, overtemperature, and power bridge faults and can be configured to protect the power MOSFETs under most short circuit conditions. Other motor drivers may be readily substituted for use in the tracking system 480 comprising an absolute positioning system.

The tracking system 480 may comprise a controlled motor drive circuit arrangement comprising a position sensor 472 according to one aspect of this disclosure. The position sensor 472 for an absolute positioning system may provide a unique position signal corresponding to the location of a displacement member. In some examples, the displacement member may represent a longitudinally movable drive member comprising a rack of drive teeth for meshing engagement with a corresponding drive gear of a gear reducer assembly. In some examples, the displacement member may represent the firing member, which could be adapted and configured to include a rack of drive teeth. In some examples, the displacement member may represent a firing bar or the I-beam, each of which can be adapted and configured to include a rack of drive teeth. Accordingly, as used herein, the term displacement member can be used generically to refer to any movable member of the surgical instrument or tool such as the drive member, the firing member, the firing bar, the I-beam, or any element that can be displaced. In one aspect, the longitudinally movable drive member can be coupled to the firing member, the firing bar, and the I-beam. Accordingly, the absolute positioning system can, in effect, track the linear displacement of the I-beam by tracking the linear displacement of the longitudinally movable drive member. In various aspects, the displacement member may be coupled to any position sensor 472 suitable for measuring linear displacement. Thus, the longitudinally movable drive member, the firing member, the firing bar, or the I-beam, or combinations thereof, may be coupled to any suitable linear displacement sensor. Linear displacement sensors may include contact or non-contact displacement sensors. Linear displacement sensors may comprise linear variable differential transformers (LVDT), differential variable reluctance transducers (DVRT), a slide potentiometer, a magnetic sensing system comprising a movable magnet and a series of linearly arranged Hall effect sensors, a magnetic sensing system comprising a fixed magnet and a series of movable, linearly arranged Hall effect sensors, an optical sensing system comprising a movable light source and a series of linearly arranged photo diodes or photo detectors, an optical sensing system comprising a fixed light source and a series of movable linearly, arranged photo diodes or photo detectors, or any combination thereof.

The electric motor 482 can include a rotatable shaft that operably interfaces with a gear assembly that is mounted in meshing engagement with a set, or rack, of drive teeth on the displacement member. A sensor element may be operably coupled to a gear assembly such that a single revolution of the position sensor 472 element corresponds to some linear longitudinal translation of the displacement member. An arrangement of gearing and sensors can be connected to the linear actuator, via a rack and pinion arrangement, or a rotary actuator, via a spur gear or other connection. A power source may supplied power to the absolute positioning system and an output indicator may display the output of the absolute positioning system. The displacement member may represent the longitudinally movable drive member comprising a rack of drive teeth formed thereon for meshing engagement with a corresponding drive gear of the gear reducer assembly. The displacement member may represent the longitudinally movable firing member, firing bar, I-beam, or combinations thereof.

A single revolution of the sensor element associated with the position sensor 472 may be equivalent to a longitudinal linear displacement d1 of the of the displacement member, where d1 is the longitudinal linear distance that the displacement member moves from point “a” to point “b” after a single revolution of the sensor element coupled to the displacement member. The sensor arrangement may be connected via a gear reduction that results in the position sensor 472 completing one or more revolutions for the fill stroke of the displacement member. The position sensor 472 may complete multiple revolutions for the full stroke of the displacement member.

A series of switches, where n is an integer greater than one, may be employed alone or in combination with a gear reduction to provide a unique position signal for more than one revolution of the position sensor 472. The state of the switches may be fed back to the microcontroller 461 that applies logic to determine a unique position signal corresponding to the longitudinal linear displacement d1+d2+ . . . dn of the displacement member. The output of the position sensor 472 is provided to the microcontroller 461. The position sensor 472 of the sensor arrangement may comprise a magnetic sensor, an analog rotary sensor like a potentiometer, or an array of analog Hall-effect elements, which output a unique combination of position signals or values.

The position sensor 472 may comprise any number of magnetic sensing elements, such as, for example, magnetic sensors classified according to whether they measure the total magnetic field or the vector components of the magnetic field. The techniques used to produce both types of magnetic sensors may encompass many aspects of physics and electronics. The technologies used for magnetic field sensing may include search coil, fluxgate, optically pumped, nuclear precession, SQUID, Hall-effect, anisotropic magnetoresistance, giant magnetoresistance, magnetic tunnel junctions, giant magnetoimpedance, magnetostrictive/piezoelectric composites, magnetodiode, magnetotransistor, fiber-optic, magneto-optic, and microelectromechanical systems-based magnetic sensors, among others.

one aspect, the position sensor 472 for the tracking system 480 comprising an absolute positioning system may comprise a magnetic rotary absolute positioning system. The position sensor 472 may be implemented as an AS5055EQFT single-chip magnetic rotary position sensor available from Austria Microsystems, AG. The position sensor 472 is interfaced with the microcontroller 461 to provide an absolute positioning system. The position sensor 472 may be a low-voltage and low-power component and includes four Hall-effect elements in an area of the position sensor 472 that may be located above a magnet. A high-resolution ADC and a smart power management controller may also be provided on the chip. A coordinate rotation digital computer (CORDIC) processor, also known as the digit-by-digit method and Volder's algorithm, may be provided to implement a simple and efficient algorithm to calculate hyperbolic and trigonometric functions that require only addition, subtraction, bitshift, and table lookup operations. The angle position, alarm bits, and magnetic field information may be transmitted over a standard serial communication interface, such as a serial peripheral interface (SPI) interface, to the microcontroller 461. The position sensor 472 may provide 12 or 14 bits of resolution. The position sensor 472 may be an AS5055 chip provided in a small QFN 16-pin 4×4×0.85 mm package.

The tracking system 480 comprising an absolute positioning system may comprise and/or be programmed to implement a feedback controller, such as a PID, state feedback, and adaptive controller. A power source converts the signal from the feedback controller into a physical input to the system: in this case the voltage. Other examples include a PWM of the voltage, current, and force. Other sensor(s) may be provided to measure physical parameters of the physical system in addition to the position measured by the position sensor 472. In some aspects, the other sensor(s) can include sensor arrangements such as those described in U.S. Pat. No. 9,345,481, titled STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM, which issued on May 24, 2016, which is herein incorporated by reference in its entirety; U.S. Patent Application Publication No. 2014/0263552, titled STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM, which published on Sep. 18, 2014, which is herein incorporated by reference in its entirety; and U.S. patent application Ser. No. 15/628,175, titled TECHNIQUES FOR ADAPTIVE CONTROL OF MOTOR VELOCITY OF A SURGICAL STAPLING AND CUTTING INSTRUMENT, filed Jun. 20, 2017, which is herein incorporated by reference in its entirety. In a digital signal processing system, an absolute positioning system is coupled to a digital data acquisition system where the output of the absolute positioning system will have a finite resolution and sampling frequency. The absolute positioning system may comprise a compare-and-combine circuit to combine a computed response with a measured response using algorithms, such as a weighted average and a theoretical control loop, that drive the computed response towards the measured response. The computed response of the physical system may take into account properties like mass, inertial, viscous friction, inductance resistance, etc., to predict what the states and outputs of the physical system will be by knowing the input.

The absolute positioning system may provide an absolute position of the displacement member upon power-up of the instrument, without retracting or advancing the displacement member to a reset (zero or home) position as may be required with conventional rotary encoders that merely count the number of steps forwards or backwards that the motor 482 has taken to infer the position of a device actuator, drive bar, knife, or the like.

A sensor 474, such as, for example, a strain gauge or a micro-strain gauge, may be configured to measure one or more parameters of the end effector, such as, for example, the amplitude of the strain exerted on the anvil during a clamping operation, which can be indicative of the closure forces applied to the anvil. The measured strain may be converted to a digital signal and provided to the processor 462. Alternatively, or in addition to the sensor 474, a sensor 476, such as, for example, a load sensor, can measure the closure force applied by the closure drive system to the anvil. The sensor 476, such as, for example, a load sensor, can measure the firing force applied to an I-beam in a firing stroke of the surgical instrument or tool. The I-beam is configured to engage a wedge sled, which is configured to upwardly cam staple drivers to force out staples into deforming contact with an anvil. The I-beam also may include a sharpened cutting edge that can be used to sever tissue as the I-beam is advanced distally by the firing bar. Alternatively, a current sensor 478 can be employed to measure the current drawn by the motor 482. The force required to advance the firing member can correspond to the current drawn by the motor 482, for example. The measured force may be converted to a digital signal and provided to the processor 462.

In one form, the strain gauge sensor 474 can be used to measure the force applied to the tissue by the end effector. A strain gauge can be coupled to the end effector to measure the force on the tissue being treated by the end effector. A system for measuring forces applied to the tissue grasped by the end effector may comprise a strain gauge sensor 474, such as, for example, a micro-strain gauge, that can be configured to measure one or more parameters of the end effector, for example. In one aspect, the strain gauge sensor 474 can measure the amplitude or magnitude of the strain exerted on a jaw member of an end effector during a clamping operation, which can be indicative of the tissue compression. The measured strain can be converted to a digital signal and provided to a processor 462 of the microcontroller 461. A load sensor 476 can measure the force used to operate the knife element, for example, to cut the tissue captured between the anvil and the staple cartridge. A magnetic field sensor can be employed to measure the thickness of the captured tissue. The measurement of the magnetic field sensor also may be converted to a digital signal and provided to the processor 462.

The measurements of the tissue compression, the tissue thickness, and/or the force required to close the end effector on the tissue, as respectively measured by the sensors 474, 476, can be used by the microcontroller 461 to characterize the selected position of the firing member and/or the corresponding value of the speed of the firing member. In one instance, a memory 468 may store a technique, an equation, and/or a lookup table which can be employed by the microcontroller 461 in the assessment.

The control system 470 of the surgical instrument or tool also may comprise wired or wireless communication circuits to communicate with the modular communication hub 203 as shown in FIGS. 5 and 6.

FIG. 8 illustrates a surgical instrument or tool comprising a plurality of motors which can be activated to perform various functions. In certain instances, a first motor can be activated to perform a first function, a second motor can be activated to perform a second function, a third motor can be activated to perform a third function, a fourth motor can be activated to perform a fourth function, and so on. In certain instances, the plurality of motors of robotic surgical instrument 600 can be individually activated to cause firing, closure, and/or articulation motions in the end effector. The firing, closure, and/or articulation motions can be transmitted to the end effector through a shaft assembly, for example.

In certain instances, the surgical instrument system or tool may include a firing motor 602. The firing motor 602 may be operably coupled to a firing motor drive assembly 604 which can be configured to transmit firing motions, generated by the motor 602 to the end effector, in particular to displace the I-beam element. In certain instances, the firing motions generated by the motor 602 may cause the staples to be deployed from the staple cartridge into tissue captured by the end effector and/or the cutting edge of the I-beam element to be advanced to cut the captured tissue, for example. The I-beam element may be retracted by reversing the direction of the motor 602.

In certain instances, the surgical instrument or tool may include a closure motor 603. The closure motor 603 may be operably coupled to a closure motor drive assembly 605 which can be configured to transmit closure motions, generated by the motor 603 to the end effector, in particular to displace a closure tube to close the anvil and compress tissue between the anvil and the staple cartridge. The closure motions may cause the end effector to transition from an open configuration to an approximated configuration to capture tissue, for example. The end effector may be transitioned to an open position by reversing the direction of the motor 603.

In certain instances, the surgical instrument or tool may include one or more articulation motors 606 a, 606 b, for example. The motors 606 a, 606 b may be operably coupled to respective articulation motor drive assemblies 608 a, 608 b, which can be configured to transmit articulation motions generated by the motors 606 a, 606 b to the end effector. In certain instances, the articulation motions may cause the end effector to articulate relative to the shaft, for example.

As described herein, the surgical instrument or tool may include a plurality of motors which may be configured to perform various independent functions. In certain instances, the plurality of motors of the surgical instrument or tool can be individually or separately activated to perform one or more functions while the other motors remain inactive. For example, the articulation motors 606 a, 606 b can be activated to cause the end effector to be articulated while the firing motor 602 remains inactive. Alternatively, the firing motor 602 can be activated to fire the plurality of staples, and/or to advance the cutting edge, while the articulation motor 606 remains inactive. Furthermore, the closure motor 603 may be activated simultaneously with the firing motor 602 to cause the closure tube and the I-beam element to advance distally as described in more detail hereinbelow.

In certain instances, the surgical instrument or tool may include a common control module 610 which can be employed with a plurality of motors of the surgical instrument or tool. In certain instances, the common control module 610 may accommodate one of the plurality of motors at a time. For example, the common control module 610 can be couplable to and separable from the plurality of motors of the robotic surgical instrument individually. In certain instances, a plurality of the motors of the surgical instrument or tool may share one or more common control modules such as the common control module 610. In certain instances, a plurality of motors of the surgical instrument or tool can be individually and selectively engaged with the common control module 610. In certain instances, the common control module 610 can be selectively switched from interfacing with one of a plurality of motors of the surgical instrument or tool to interfacing with another one of the plurality of motors of the surgical instrument or tool.

In at least one example, the common control module 610 can be selectively switched between operable engagement with the articulation motors 606 a, 606 b and operable engagement with either the firing motor 602 or the closure motor 603. In at least one example, as illustrated in FIG. 8, a switch 614 can be moved or transitioned between a plurality of positions and/or states. In a first position 616, the switch 614 may electrically couple the common control module 610 to the firing motor 602; in a second position 617, the switch 614 may electrically couple the common control module 610 to the closure motor 603; in a third position 618 a, the switch 614 may electrically couple the common control module 610 to the first articulation motor 606 a; and in a fourth position 618 b, the switch 614 may electrically couple the common control module 610 to the second articulation motor 606 b, for example. In certain instances, separate common control modules 610 can be electrically coupled to the firing motor 602, the closure motor 603, and the articulations motor 606 a, 606 b at the same time. In certain instances, the switch 614 may be a mechanical switch, an electromechanical switch, a solid-state switch, or any suitable switching mechanism.

Each of the motors 602, 603, 606 a, 606 b may comprise a torque sensor to measure the output torque on the shaft of the motor. The force on an end effector may be sensed in any conventional manner, such as by force sensors on the outer sides of the jaws or by a torque sensor for the motor actuating the laws.

In various instances, as illustrated in FIG. 8, the common control module 610 may comprise a motor driver 626 which may comprise one or more H-Bridge FETs. The motor driver 626 may modulate the power transmitted from a power source 628 to a motor coupled to the common control module 610 based on input from a microcontroller 620 (the “controller”), for example. In certain instances, the microcontroller 620 can be employed to determine the current drawn by the motor, for example, while the motor is coupled to the common control module 610, as described herein.

In certain instances, the microcontroller 620 may include a microprocessor 622 (the “processor”) and one or more non-transitory computer-readable mediums or memory units 624 (the “memory”). In certain instances, the memory 624 may store various program instructions, which when executed may cause the processor 622 to perform a plurality of functions and/or calculations described herein. In certain instances, one or more of the memory units 624 may be coupled to the processor 622, for example.

In certain instances, the power source 628 can be employed to supply power to the microcontroller 620, for example. In certain instances, the power source 628 may comprise a battery (or “battery pack” or “power pack”), such as a lithium-ion battery, for example. In certain instances, the battery pack may be configured to be releasably mounted to a handle for supplying power to the surgical instrument 600. A number of battery cells connected in series may be used as the power source 628. In certain instances, the power source 628 may be replaceable and/or rechargeable, for example.

In various instances, the processor 622 may control the motor driver 626 to control the position, direction of rotation, and/or velocity of a motor that is coupled to the common control module 610. In certain instances, the processor 622 can signal the motor driver 626 to stop and/or disable a motor that is coupled to the common control module 610. It should be understood that the term “processor” as used herein includes any suitable microprocessor, microcontroller, or other basic computing device that incorporates the functions of a computer's central processing unit (CPU) on an integrated circuit or, at most, a few integrated circuits. The processor can be a multipurpose, programmable device that accepts digital data as input, processes it according to instructions stored in its memory, and provides results as output. It can be an example of sequential digital logic, as it may have internal memory. Processors may operate on numbers and symbols represented in the binary numeral system.

The processor 622 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In certain instances, the microcontroller 620 may be an LM 4F230H5QR, available from Texas Instruments, for example. In at least one example, the Texas Instruments LM4F230H5QR is an ARM Cortex-M4F Processor Core comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle SRAM, an internal ROM loaded with StellarisWare® software, a 2 KB EEPROM, one or more PWM modules, one or more QEI analogs, one or more 12-bit ADCs with 12 analog input channels, among other features that are readily available for the product datasheet. Other microcontrollers may be readily substituted for use with the module 4410. Accordingly, the present disclosure should not be limited in this context.

The memory 624 may include program instructions for controlling each of the motors of the surgical instrument 600 that are couplable to the common control module 610. For example, the memory 624 may include program instructions for controlling the firing motor 602, the closure motor 603, and the articulation motors 606 a, 606 b. Such program instructions may cause the processor 622 to control the firing, closure, and articulation functions in accordance with inputs from algorithms or control programs of the surgical instrument or tool.

One or more mechanisms and/or sensors such as, for example, sensors 630 can be employed to alert the processor 622 to the program instructions that should be used in a particular setting. For example, the sensors 630 may alert the processor 622 to use the program instructions associated with firing, closing, and articulating the end effector. In certain instances, the sensors 630 may comprise position sensors which can be employed to sense the position of the switch 614, for example. Accordingly, the processor 622 may use the program instructions associated with firing the I-beam of the end effector upon detecting, through the sensors 630 for example, that the switch 614 is in the first position 616; the processor 622 may use the program instructions associated with closing the anvil upon detecting, through the sensors 630 for example, that the switch 614 is in the second position 617; and the processor 622 may use the program instructions associated with articulating the end effector upon detecting, through the sensors 630 for example, that the switch 614 is in the third or fourth position 618 a, 618 b.

FIG. 9 illustrates a diagram of a situationally aware surgical system 5100, in accordance with at least one aspect of the present disclosure. In some exemplifications, the data sources 5126 may include, for example, the modular devices 5102 (which can include sensors configured to detect parameters associated with the patient and/or the modular device itself), databases 5122 (e.g., an EMR database containing patient records), and patient monitoring devices 5124 (e.g., a blood pressure (BP) monitor and an electrocardiography (EKG) monitor). The surgical hub 5104 can be configured to derive the contextual information pertaining to the surgical procedure from the data based upon, for example, the particular combination(s) of received data or the particular order in which the data is received from the data sources 5126. The contextual information inferred from the received data can include, for example, the type of surgical procedure being performed, the particular step of the surgical procedure that the surgeon is performing, the type of tissue being operated on, or the body cavity that is the subject of the procedure. This ability by some aspects of the surgical hub 5104 to derive or infer information related to the surgical procedure from received data can be referred to as “situational awareness.” In an exemplification, the surgical hub 5104 can incorporate a situational awareness system, which is the hardware and/or programming associated with the surgical hub 5104 that derives contextual information pertaining to the surgical procedure from the received data.

The situational awareness system of the surgical hub 5104 can be configured to derive the contextual information from the data received from the data sources 5126 in a variety of different ways. In an exemplification, the situational awareness system can include a pattern recognition system, or machine learning system (e.g., an artificial neural network), that has been trained on training data to correlate various inputs (e.g., data from databases 5122, patient monitoring devices 5124, and/or modular devices 5102) to corresponding contextual information regarding a surgical procedure. In other words, a machine learning system can be trained to accurately derive contextual information regarding a surgical procedure from the provided inputs. In examples, the situational awareness system can include a lookup table storing pre-characterized contextual information regarding a surgical procedure in association with one or more inputs (or ranges of inputs) corresponding to the contextual information. In response to a query with one or more inputs, the lookup table can return the corresponding contextual information for the situational awareness system for controlling the modular devices 5102. In examples, the contextual information received by the situational awareness system of the surgical hub 5104 can be associated with a particular control adjustment or set of control adjustments for one or more modular devices 5102. In examples, the situational awareness system can include a further machine learning system, lookup table, or other such system, which generates or retrieves one or more control adjustments for one or more modular devices 5102 when provided the contextual information as input.

A surgical hub 5104 incorporating a situational awareness system can provide a number of benefits for the surgical system 5100. One benefit may include improving the interpretation of sensed and collected data, which would in turn improve the processing accuracy and/or the usage of the data during the course of a surgical procedure. To return to a previous example, a situationally aware surgical hub 5104 could determine what type of tissue was being operated on; therefore, when an unexpectedly high force to close the surgical instrument's end effector is detected, the situationally aware surgical hub 5104 could correctly ramp up or ramp down the motor of the surgical instrument for the type of tissue.

The type of tissue being operated can affect the adjustments that are made to the compression rate and load thresholds of a surgical stapling and cutting instrument for a particular tissue gap measurement. A situationally aware surgical hub 5104 could infer whether a surgical procedure being performed is a thoracic or an abdominal procedure, allowing the surgical hub 5104 to determine whether the tissue clamped by an end effector of the surgical stapling and cutting instrument is lung (for a thoracic procedure) or stomach (for an abdominal procedure) tissue. The surgical hub 5104 could then adjust the compression rate and load thresholds of the surgical stapling and cutting instrument appropriately for the type of tissue.

The type of body cavity being operated in during an insufflation procedure can affect the function of a smoke evacuator. A situationally aware surgical hub 5104 could determine whether the surgical site is under pressure (by determining that the surgical procedure is utilizing insufflation) and determine the procedure type. As a procedure type can be generally performed in a specific body cavity, the surgical hub 5104 could then control the motor rate of the smoke evacuator appropriately for the body cavity being operated in. Thus, a situationally aware surgical hub 5104 could provide a consistent amount of smoke evacuation for both thoracic and abdominal procedures.

The type of procedure being performed can affect the optimal energy level for an ultrasonic surgical instrument or radio frequency (RF) electrosurgical instrument to operate at. Arthroscopic procedures, for example, may require higher energy levels because the end effector of the ultrasonic surgical instrument or RF electrosurgical instrument is immersed in fluid. A situationally aware surgical hub 5104 could determine whether the surgical procedure is an arthroscopic procedure. The surgical hub 5104 could then adjust the RF power level or the ultrasonic amplitude of the generator (i.e., “energy level”) to compensate for the fluid filled environment. Relatedly, the type of tissue being operated on can affect the optimal energy level for an ultrasonic surgical instrument or RF electrosurgical instrument to operate at. A situationally aware surgical hub 5104 could determine what type of surgical procedure is being performed and then customize the energy level for the ultrasonic surgical instrument or RF electrosurgical instrument, respectively, according to the expected tissue profile for the surgical procedure. Furthermore, a situationally aware surgical hub 5104 can be configured to adjust the energy level for the ultrasonic surgical instrument or RF electrosurgical instrument throughout the course of a surgical procedure, rather than just on a procedure-by-procedure basis. A situationally aware surgical hub 5104 could determine what step of the surgical procedure is being performed or will subsequently be performed and then update the control algorithms for the generator and/or ultrasonic surgical instrument or RF electrosurgical instrument to set the energy level at a value appropriate for the expected tissue type according to the surgical procedure step.

In examples, data can be drawn from additional data sources 5126 to improve the conclusions that the surgical hub 5104 draws from one data source 5126. A situationally aware surgical hub 5104 could augment data that it receives from the modular devices 5102 with contextual information that it has built up regarding the surgical procedure from other data sources 5126. For example, a situationally aware surgical hub 5104 can be configured to determine whether hemostasis has occurred (i.e., whether bleeding at a surgical site has stopped) according to video or image data received from a medical imaging device. However, in some cases the video or image data can be inconclusive. Therefore, in an exemplification, the surgical hub 5104 can be further configured to compare a physiologic measurement (e.g., blood pressure sensed by a BP monitor communicably connected to the surgical hub 5104) with the visual or image data of hemostasis (e.g., from a medical imaging device 124 (FIG. 2) communicably coupled to the surgical hub 5104) to make a determination on the integrity of the staple line or tissue weld. In other words, the situational awareness system of the surgical hub 5104 can consider the physiological measurement data to provide additional context in analyzing the visualization data. The additional context can be useful when the visualization data may be inconclusive or incomplete on its own.

For example, a situationally aware surgical hub 5104 could proactively activate the generator to which an RF electrosurgical instrument is connected if it determines that a subsequent step of the procedure requires the use of the instrument. Proactively activating the energy source can allow the instrument to be ready for use a soon as the preceding step of the procedure is completed.

The situationally aware surgical hub 5104 could determine whether the current or subsequent step of the surgical procedure requires a different view or degree of magnification on the display according to the feature(s) at the surgical site that the surgeon is expected to need to view. The surgical hub 5104 could then proactively change the displayed view (supplied by, e.g., a medical imaging device for the visualization system 108) accordingly so that the display automatically adjusts throughout the surgical procedure.

The situationally aware surgical hub 5104 could determine which step of the surgical procedure is being performed or will subsequently be performed and whether particular data or comparisons between data will be required for that step of the surgical procedure. The surgical hub 5104 can be configured to automatically call up data screens based upon the step of the surgical procedure being performed, without waiting for the surgeon to ask for the particular information.

Errors may be checked during the setup of the surgical procedure or during the course of the surgical procedure. For example, the situationally aware surgical hub 5104 could determine whether the operating theater is setup properly or optimally for the surgical procedure to be performed. The surgical hub 5104 can be configured to determine the type of surgical procedure being performed, retrieve the corresponding checklists, product location, or setup needs (e.g., from a memory), and then compare the current operating theater layout to the standard layout for the type of surgical procedure that the surgical hub 5104 determines is being performed. In some exemplifications, the surgical hub 5104 can be configured to compare the list of items for the procedure and/or a list of devices paired with the surgical hub 5104 to a recommended or anticipated manifest of items and/or devices for the given surgical procedure. If there are any discontinuities between the lists, the surgical hub 5104 can be configured to provide an alert indicating that a particular modular device 5102, patient monitoring device 5124, and/or other surgical item is missing. In some exemplifications, the surgical hub 5104 can be configured to determine the relative distance or position of the modular devices 5102 and patient monitoring devices 5124 via proximity sensors, for example. The surgical hub 5104 can compare the relative positions of the devices to a recommended or anticipated layout for the particular surgical procedure. If there are any discontinuities between the layouts, the surgical hub 5104 can be configured to provide an alert indicating that the current layout for the surgical procedure deviates from the recommended layout.

The situationally aware surgical hub 5104 could determine whether the surgeon (or other medical personnel) was making an error or otherwise deviating from the expected course of action during the course of a surgical procedure. For example, the surgical hub 5104 can be configured to determine the type of surgical procedure being performed, retrieve the corresponding list of steps or order of equipment usage (e.g., from a memory), and then compare the steps being performed or the equipment being used during the course of the surgical procedure to the expected steps or equipment for the type of surgical procedure that the surgical hub 5104 determined is being performed. In some exemplifications, the surgical hub 5104 can be configured to provide an alert indicating that an unexpected action is being performed or an unexpected device is being utilized at the particular step in the surgical procedure.

The surgical instruments (and other modular devices 5102) may be adjusted for the particular context of each surgical procedure (such as adjusting to different tissue types) and validating actions during a surgical procedure. Next steps, data, and display adjustments may be provided to surgical instruments (and other modular devices 5102) in the surgical theater according to the specific context of the procedure.

FIG. 10 illustrates a timeline 5200 of an illustrative surgical procedure and the contextual information that a surgical hub 5104 can derive from the data received from the data sources 5126 at each step in the surgical procedure. In the following description of the timeline 5200 illustrated in FIG. 9, reference should also be made to FIG. 9. The timeline 5200 may depict the typical steps that would be taken by the nurses, surgeons, and other medical personnel during the course of a lung segmentectomy procedure, beginning with setting up the operating theater and ending with transferring the patient to a post-operative recovery room. The situationally aware surgical hub 5104 may receive data from the data sources 5126 throughout the course of the surgical procedure, including data generated each time medical personnel utilize a modular device 5102 that is paired with the surgical hub 5104. The surgical hub 5104 can receive this data from the paired modular devices 5102 and other data sources 5126 and continually derive inferences (i.e., contextual information) about the ongoing procedure as new data is received, such as which step of the procedure is being performed at any given time. The situational awareness system of the surgical hub 5104 can be able to, for example, record data pertaining to the procedure for generating reports, verify the steps being taken by the medical personnel, provide data or prompts (e.g., via a display screen) that may be pertinent for the particular procedural step, adjust modular devices 5102 based on the context (e.g., activate monitors, adjust the FOV of the medical imaging device, or change the energy level of an ultrasonic surgical instrument or RF electrosurgical instrument), and take any other such action described herein.

As the first step 5202 in this illustrative procedure, the hospital staff members may retrieve the patient's EMR from the hospital's EMR database. Based on select patient data in the EMR, the surgical hub 5104 determines that the procedure to be performed is a thoracic procedure. Second 5204, the staff members may scan the incoming medical supplies for the procedure. The surgical hub 5104 cross-references the scanned supplies with a list of supplies that can be utilized in various types of procedures and confirms that the mix of supplies corresponds to a thoracic procedure. Further, the surgical hub 5104 may also be able to determine that the procedure is not a wedge procedure (because the incoming supplies either lack certain supplies that are necessary for a thoracic wedge procedure or do not otherwise correspond to a thoracic wedge procedure). Third 5206, the medical personnel may scan the patient band via a scanner 5128 that is communicably connected to the surgical hub 5104. The surgical hub 5104 can then confirm the patient's identity based on the scanned data. Fourth 5208, the medical staff turns on the auxiliary equipment. The auxiliary equipment being utilized can vary according to the type of surgical procedure and the techniques to be used by the surgeon, but in this illustrative case they include a smoke evacuator, insufflator, and medical imaging device. When activated, the auxiliary equipment that are modular devices 5102 can automatically pair with the surgical hub 5104 that may be located within a particular vicinity of the modular devices 5102 as part of their initialization process. The surgical hub 5104 can then derive contextual information about the surgical procedure by detecting the types of modular devices 5102 that pair with it during this pre-operative or initialization phase. In this particular example, the surgical hub 5104 may determine that the surgical procedure is a VATS procedure based on this particular combination of paired modular devices 5102. Based on the combination of the data from the patient's EMR, the list of medical supplies to be used in the procedure, and the type of modular devices 5102 that connect to the hub, the surgical hub 5104 can generally infer the specific procedure that the surgical team will be performing. Once the surgical hub 5104 knows what specific procedure is being performed, the surgical hub 5104 can then retrieve the steps of that procedure from a memory or from the cloud and then cross-reference the data it subsequently receives from the connected data sources 5126 (e.g., modular devices 5102 and patient monitoring devices 5124) to infer what step of the surgical procedure the surgical team is performing. Fifth 5210, the staff members attach the EKG electrodes and other patient monitoring devices 5124 to the patient. The EKG electrodes and other patient monitoring devices 5124 may pair with the surgical hub 5104. As the surgical hub 5104 begins receiving data from the patient monitoring devices 5124, the surgical hub 5104 may confirm that the patient is in the operating theater, as described in the process 5207, for example. Sixth 5212, the medical personnel may induce anesthesia in the patient. The surgical hub 5104 can infer that the patient is under anesthesia based on data from the modular devices 5102 and/or patient monitoring devices 5124, including EKG data, blood pressure data, ventilator data, or combinations thereof, for example. Upon completion of the sixth step 5212, the pre-operative portion of the lung segmentectomy procedure is completed and the operative portion begins.

Seventh 5214, the patient's lung that is being operated on may be collapsed (while ventilation is switched to the contralateral lung). The surgical hub 5104 can infer from the ventilator data that the patient's lung has been collapsed, for example. The surgical hub 5104 can infer that the operative portion of the procedure has commenced as it can compare the detection of the patient's lung collapsing to the expected steps of the procedure (which can be accessed or retrieved previously) and thereby determine that collapsing the lung can be the first operative step in this particular procedure. Eighth 5216, the medical imaging device 5108 (e.g., a scope) may be inserted and video from the medical imaging device may be initiated. The surgical hub 5104 may receive the medical imaging device data (i.e., video or image data) through its connection to the medical imaging device. Upon receipt of the medical imaging device data, the surgical hub 5104 can determine that the laparoscopic portion of the surgical procedure has commenced. Further, the surgical hub 5104 can determine that the particular procedure being performed is a segmentectomy, as opposed to a lobectomy (note that a wedge procedure has already been discounted by the surgical hub 5104 based on data received at the second step 5204 of the procedure). The data from the medical imaging device 124 (FIG. 2) can be utilized to determine contextual information regarding the type of procedure being performed in a number of different ways, including by determining the angle at which the medical imaging device is oriented with respect to the visualization of the patient's anatomy, monitoring the number or medical imaging devices being utilized (i.e., that are activated and paired with the surgical hub 5104), and monitoring the types of visualization devices utilized. For example, one technique for performing a VATS lobectomy may place the camera in the lower anterior corner of the patient's chest cavity above the diaphragm, whereas one technique for performing a VATS segmentectomy places the camera in an anterior intercostal position relative to the segmental fissure. Using pattern recognition or machine learning techniques, for example, the situational awareness system can be trained to recognize the positioning of the medical imaging device according to the visualization of the patient's anatomy. An example technique for performing a VATS lobectomy may utilize a single medical imaging device. An example technique for performing a VATS segmentectomy utilizes multiple cameras. An example technique for performing a VATS segmentectomy utilizes an infrared light source (which can be communicably coupled to the surgical hub as part of the visualization system) to visualize the segmental fissure, which is not utilized in a VATS lobectomy. By tracking any or all of this data from the medical imaging device 5108, the surgical hub 5104 can thereby determine the specific type of surgical procedure being performed and/or the technique being used for a particular type of surgical procedure.

Ninth 5218, the surgical team may begin the dissection step of the procedure. The surgical hub 5104 can infer that the surgeon is in the process of dissecting to mobilize the patient's lung because it receives data from the RF or ultrasonic generator indicating that an energy instrument is being fired. The surgical hub 5104 can cross-reference the received data with the retrieved steps of the surgical procedure to determine that an energy instrument being fired at this point in the process (i.e., after the completion of the previously discussed steps of the procedure) corresponds to the dissection step. Tenth 5220, the surgical team may proceed to the ligation step of the procedure. The surgical hub 5104 can infer that the surgeon is ligating arteries and veins because it may receive data from the surgical stapling and cutting instrument indicating that the instrument is being fired. Similar to the prior step, the surgical hub 5104 can derive this inference by cross-referencing the receipt of data from the surgical stapling and cutting instrument with the retrieved steps in the process. Eleventh 5222, the segmentectomy portion of the procedure can be performed. The surgical hub 5104 can infer that the surgeon is transecting the parenchyma based on data from the surgical stapling and cutting instrument, including data from its cartridge. The cartridge data can correspond to the size or type of staple being fired by the instrument, for example. As different types of staples are utilized for different types of tissues, the cartridge data can thus indicate the type of tissue being stapled and/or transected. In this case, the type of staple being fired is utilized for parenchyma (or other similar tissue types), which allows the surgical hub 5104 to infer that the segmentectomy portion of the procedure is being performed. Twelfth 5224, the node dissection step is then performed. The surgical hub 5104 can infer that the surgical team is dissecting the node and performing a leak test based on data received from the generator indicating that an RF or ultrasonic instrument is being fired. For this particular procedure, an RF or ultrasonic instrument being utilized after parenchyma was transected corresponds to the node dissection step, which allows the surgical hub 5104 to make this inference. It should be noted that surgeons regularly switch back and forth between surgical stapling/cutting instruments and surgical energy (e.g., RF or ultrasonic) instruments depending upon the particular step in the procedure because different instruments are better adapted for particular tasks. Therefore, the particular sequence in which the stapling/cutting instruments and surgical energy instruments are used can indicate what step of the procedure the surgeon is performing. Upon completion of the twelfth step 5224, the incisions and closed up and the post-operative portion of the procedure may begin.

Thirteenth 5226, the patient's anesthesia can be reversed. The surgical hub 5104 can infer that the patient is emerging from the anesthesia based on the ventilator data (i.e., the patient's breathing rate begins increasing), for example. Lastly, the fourteenth step 5228 may be that the medical personnel remove the various patient monitoring devices 5124 from the patient. The surgical hub 5104 can thus infer that the patient is being transferred to a recovery room when the hub loses EKG, BP, and other data from the patient monitoring devices 5124. As can be seen from the description of this illustrative procedure, the surgical hub 5104 can determine or infer when each step of a given surgical procedure is taking place according to data received from the various data sources 5126 that are communicably coupled to the surgical hub 5104.

In addition to utilizing the patient data from EMR database(s) to infer the type of surgical procedure that is to be performed, as illustrated in the first step 5202 of the timeline 5200 depicted in FIG. 10, the patient data can also be utilized by a situationally aware surgical hub 5104 to generate control adjustments for the paired modular devices 5102.

FIG. 11 is a block diagram of the computer-implemented interactive surgical system, in accordance with at least one aspect of the present disclosure. In one aspect, the computer-implemented interactive surgical system may be configured to monitor and analyze data related to the operation of various surgical systems that include surgical hubs, surgical instruments, robotic devices and operating theaters or healthcare facilities. The computer-implemented interactive surgical system may comprise a cloud-based analytics system. Although the cloud-based analytics system may be described as a surgical system, it may not be necessarily limited as such and could be a cloud-based medical system generally. As illustrated in FIG. 11, the cloud-based analytics system may comprise a plurality of surgical instruments 7012 (may be the same or similar to instruments 112), a plurality of surgical hubs 7006 (may be the same or similar to hubs 106), and a surgical data network 7001 (may be the same or similar to network 201) to couple the surgical hubs 7006 to the cloud 7004 (may be the same or similar to cloud 204). Each of the plurality of surgical hubs 7006 may be communicatively coupled to one or more surgical instruments 7012. The hubs 7006 may also be communicatively coupled to the cloud 7004 of the computer-implemented interactive surgical system via the network 7001. The cloud 7004 may be a remote centralized source of hardware and software for storing, manipulating, and communicating data generated based on the operation of various surgical systems. As shown in FIG. 11, access to the cloud 7004 may be achieved via the network 7001, which may be the Internet or some other suitable computer network. Surgical hubs 7006 that may be coupled to the cloud 7004 can be considered the client side of the cloud computing system (i.e., cloud-based analytics system). Surgical instruments 7012 may be paired with the surgical hubs 7006 for control and implementation of various surgical procedures or operations as described herein.

In addition, surgical instruments 7012 may comprise transceivers for data transmission to and from their corresponding surgical hubs 7006 (which may also comprise transceivers). Combinations of surgical instruments 7012 and corresponding hubs 7006 may indicate particular locations, such as operating theaters in healthcare facilities (e.g., hospitals), for providing medical operations. For example, the memory of a surgical hub 7006 may store location data. As shown in FIG. 11, the cloud 7004 comprises central servers 7013 (may be same or similar to remote server 7013), hub application servers 7002, data analytics modules 7034, and an input/output (“I/O”) interface 7006. The central servers 7013 of the cloud 7004 collectively administer the cloud computing system, which includes monitoring requests by client surgical hubs 7006 and managing the processing capacity of the cloud 7004 for executing the requests. Each of the central servers 7013 may comprise one or more processors 7008 coupled to suitable memory devices 7010 which can include volatile memory such as random-access memory (RAM) and non-volatile memory such as magnetic storage devices. The memory devices 7010 may comprise machine executable instructions that when executed cause the processors 7008 to execute the data analytics modules 7034 for the cloud-based data analysis, operations, recommendations and other operations described below. Moreover, the processors 7008 can execute the data analytics modules 7034 independently or in conjunction with hub applications independently executed by the hubs 7006. The central servers 7013 also may comprise aggregated medical data databases 2212, which can reside in the memory 2210.

Based on connections to various surgical hubs 7006 via the network 7001, the cloud 7004 can aggregate data from specific data generated by various surgical instruments 7012 and their corresponding hubs 7006. Such aggregated data may be stored within the aggregated medical databases 7012 of the cloud 7004. In particular, the cloud 7004 may advantageously perform data analysis and operations on the aggregated data to yield insights and/or perform functions that individual hubs 7006 could not achieve on their own. To this end, as shown in FIG. 11, the cloud 7004 and the surgical hubs 7006 are communicatively coupled to transmit and receive information. The I/O interface 7006 is connected to the plurality of surgical hubs 7006 via the network 7001. In this way, the I/O interface 7006 can be configured to transfer information between the surgical hubs 7006 and the aggregated medical data databases 7011. Accordingly, the I/O interface 7006 may facilitate read/write operations of the cloud-based analytics system. Such read/write operations may be executed in response to requests from hubs 7006. These requests could be transmitted to the hubs 7006 through the hub applications. The I/O interface 7006 may include one or more high speed data ports, which may include universal serial bus (USB) ports, IEEE 1394 ports, as well as Wi-Fi and Bluetooth I/O interfaces for connecting the cloud 7004 to hubs 7006. The hub application servers 7002 of the cloud 7004 may be configured to host and supply shared capabilities to software applications (e.g., hub applications) executed by surgical hubs 7006. For example, the hub application servers 7002 may manage requests made by the hub applications through the hubs 7006, control access to the aggregated medical data databases 7011, and perform load balancing. The data analytics modules 7034 are described in further detail with reference to FIG. 12.

The particular cloud computing system configuration described in the present disclosure may be specifically designed to address various issues arising in the context of medical operations and procedures performed using medical devices, such as the surgical instruments 7012, 112. In particular, the surgical instruments 7012 may be digital surgical devices configured to interact with the cloud 7004 for implementing techniques to improve the performance of surgical operations. Various surgical instruments 7012 and/or surgical hubs 7006 may comprise touch-controlled user interfaces such that clinicians may control aspects of interaction between the surgical instruments 7012 and the cloud 7004. Other suitable user interfaces for control such as auditory controlled user interfaces can also be used.

FIG. 12 is a block diagram which illustrates the functional architecture of the computer-implemented interactive surgical system, in accordance with at least one aspect of the present disclosure. The cloud-based analytics system may include a plurality of data analytics modules 7034 that may be executed by the processors 7008 of the cloud 7004 for providing data analytic solutions to problems specifically arising in the medical field. As shown in FIG. 12, the functions of the cloud-based data analytics modules 7034 may be assisted via hub applications 7014 hosted by the hub application servers 7002 that may be accessed on surgical hubs 7006. The cloud processors 7008 and hub applications 7014 may operate in conjunction to execute the data analytics modules 7034. Application program interfaces (APIs) 7016 may define the set of protocols and routines corresponding to the hub applications 7014. Additionally, the APIs 7016 may manage the storing and retrieval of data into and from the aggregated medical databases 7012 for the operations of the applications 7014. The caches 7018 may also store data (e.g., temporarily) and may be coupled to the APIs 7016 for more efficient retrieval of data used by the applications 7014. The data analytics modules 7034 in FIG. 12 may include modules for resource optimization 7020, data collection and aggregation 7022, authorization and security 7024, control program updating 7026, patient outcome analysis 7028, recommendations 7030, and data sorting and prioritization 7032. Other suitable data analytics modules could also be implemented by the cloud 7004, according to some aspects. In one aspect, the data analytics modules may be used for specific recommendations based on analyzing trends, outcomes, and other data.

For example, the data collection and aggregation module 7022 could be used to generate self-describing data (e.g., metadata) including identification of notable features or configuration (e.g., trends), management of redundant data sets, and storage of the data in paired data sets which can be grouped by surgery but not necessarily keyed to actual surgical dates and surgeons. In particular, pair data sets generated from operations of surgical instruments 7012 can comprise applying a binary classification, e.g., a bleeding or a non-bleeding event. More generally, the binary classification may be characterized as either a desirable event (e.g., a successful surgical procedure) or an undesirable event (e.g., a misfired or misused surgical instrument 7012). The aggregated self-describing data may correspond to individual data received from various groups or subgroups of surgical hubs 7006. Accordingly, the data collection and aggregation module 7022 can generate aggregated metadata or other organized data based on raw data received from the surgical hubs 7006. To this end, the processors 7008 can be operationally coupled to the hub applications 7014 and aggregated medical data databases 7011 for executing the data analytics modules 7034. The data collection and aggregation module 7022 may store the aggregated organized data into the aggregated medical data databases 2212.

The resource optimization module 7020 can be configured to analyze this aggregated data to determine an optimal usage of resources for a particular or group of healthcare facilities. For example, the resource optimization module 7020 may determine an optimal order point of surgical stapling instruments 7012 for a group of healthcare facilities based on corresponding predicted demand of such instruments 7012. The resource optimization module 7020 might also assess the resource usage or other operational configurations of various healthcare facilities to determine whether resource usage could be improved. Similarly, the recommendations module 7030 can be configured to analyze aggregated organized data from the data collection and aggregation module 7022 to provide recommendations. For example, the recommendations module 7030 could recommend to healthcare facilities (e.g., medical service providers such as hospitals) that a particular surgical instrument 7012 should be upgraded to an improved version based on a higher than expected error rate, for example. Additionally, the recommendations module 7030 and/or resource optimization module 7020 could recommend better supply chain parameters such as product reorder points and provide suggestions of different surgical instrument 7012, uses thereof, or procedure steps to improve surgical outcomes. The healthcare facilities can receive such recommendations via corresponding surgical hubs 7006. More specific recommendations regarding parameters or configurations of various surgical instruments 7012 can also be provided. Hubs 7006 and/or surgical instruments 7012 each could also have display screens that display data or recommendations provided by the cloud 7004.

The patient outcome analysis module 7028 can analyze surgical outcomes associated with currently used operational parameters of surgical instruments 7012. The patient outcome analysis module 7028 may also analyze and assess other potential operational parameters. In this connection, the recommendations module 7030 could recommend using these other potential operational parameters based on yielding better surgical outcomes, such as better sealing or less bleeding. For example, the recommendations module 7030 could transmit recommendations to a surgical 7006 regarding when to use a particular cartridge for a corresponding stapling surgical instrument 7012. Thus, the cloud-based analytics system, while controlling for common variables, may be configured to analyze the large collection of raw data and to provide centralized recommendations over multiple healthcare facilities (advantageously determined based on aggregated data). For example, the cloud-based analytics system could analyze, evaluate, and/or aggregate data based on type of medical practice, type of patient, number of patients, geographic similarity between medical providers, which medical providers/facilities use similar types of instruments, etc., in a way that no single healthcare facility alone would be able to analyze independently. The control program updating module 7026 could be configured to implement various surgical instrument 7012 recommendations when corresponding control programs are updated. For example, the patient outcome analysis module 7028 could identify correlations linking specific control parameters with successful (or unsuccessful) results. Such correlations may be addressed when updated control programs are transmitted to surgical instruments 7012 via the control program updating module 7026. Updates to instruments 7012 that may be transmitted via a corresponding hub 7006 may incorporate aggregated performance data that was gathered and analyzed by the data collection and aggregation module 7022 of the cloud 7004. Additionally, the patient outcome analysis module 7028 and recommendations module 7030 could identify improved methods of using instruments 7012 based on aggregated performance data.

The cloud-based analytics system may include security features implemented by the cloud 7004. These security features may be managed by the authorization and security module 7024. Each surgical hub 7006 can have associated unique credentials such as username, password, and other suitable security credentials. These credentials could be stored in the memory 7010 and be associated with a permitted cloud access level. For example, based on providing accurate credentials, a surgical hub 7006 may be granted access to communicate with the cloud to a predetermined extent (e.g., may only engage in transmitting or receiving certain defined types of information). To this end, the aggregated medical data databases 7011 of the cloud 7004 may comprise a database of authorized credentials for verifying the accuracy of provided credentials. Different credentials may be associated with varying levels of permission for interaction with the cloud 7004, such as a predetermined access level for receiving the data analytics generated by the cloud 7004. Furthermore, for security purposes, the cloud could maintain a database of hubs 7006, instruments 7012, and other devices that may comprise a “black list” of prohibited devices. In particular, a surgical hubs 7006 listed on the black list may not be permitted to interact with the cloud, while surgical instruments 7012 listed on the black list may not have functional access to a corresponding hub 7006 and/or may be prevented from fully functioning when paired to its corresponding hub 7006. Additionally, or alternatively, the cloud 7004 may flag instruments 7012 based on incompatibility or other specified criteria. In this manner, counterfeit medical devices and improper reuse of such devices throughout the cloud-based analytics system can be identified and addressed.

The surgical instruments 7012 may use wireless transceivers to transmit wireless signals that may represent, for example, authorization credentials for access to corresponding hubs 7006 and the cloud 7004. Wired transceivers may also be used to transmit signals. Such authorization credentials can be stored in the respective memory devices of the surgical instruments 7012. The authorization and security module 7024 can determine whether the authorization credentials are accurate or counterfeit. The authorization and security module 7024 may also dynamically generate authorization credentials for enhanced security. The credentials could also be encrypted, such as by using hash-based encryption. Upon transmitting proper authorization, the surgical instruments 7012 may transmit a signal to the corresponding hubs 7006 and ultimately the cloud 7004 to indicate that the instruments 7012 are ready to obtain and transmit medical data. In response, the cloud 7004 may transition into a state enabled for receiving medical data for storage into the aggregated medical data databases 7011. This data transmission readiness could be indicated by a light indicator on the instruments 7012, for example. The cloud 7004 can also transmit signals to surgical instruments 7012 for updating their associated control programs. The cloud 7004 can transmit signals that are directed to a particular class of surgical instruments 7012 (e.g., electrosurgical instruments) so that software updates to control programs are only transmitted to the appropriate surgical instruments 7012. Moreover, the cloud 7004 could be used to implement system wide solutions to address local or global problems based on selective data transmission and authorization credentials. For example, if a group of surgical instruments 7012 are identified as having a common manufacturing defect, the cloud 7004 may change the authorization credentials corresponding to this group to implement an operational lockout of the group.

The cloud-based analytics system may allow for monitoring multiple healthcare facilities (e.g., medical facilities like hospitals) to determine improved practices and recommend changes (via the recommendations module 2030, for example) accordingly. Thus, the processors 7008 of the cloud 7004 can analyze data associated with an individual healthcare facility to identify the facility and aggregate the data with other data associated with other healthcare facilities in a group. Groups could be defined based on similar operating practices or geographical location, for example. In this way, the cloud 7004 may provide healthcare facility group wide analysis and recommendations. The cloud-based analytics system could also be used for enhanced situational awareness. For example, the processors 7008 may predictively model the effects of recommendations on the cost and effectiveness for a particular facility (relative to overall operations and/or various medical procedures). The cost and effectiveness associated with that particular facility can also be compared to a corresponding local region of other facilities or any other comparable facilities.

The data sorting and prioritization module 7032 may prioritize and sort data based on criticality (e.g., the severity of a medical event associated with the data, unexpectedness, suspiciousness). This sorting and prioritization may be used in conjunction with the functions of the other data analytics modules 7034 described herein to improve the cloud-based analytics and operations described herein. For example, the data sorting and prioritization module 7032 can assign a priority to the data analysis performed by the data collection and aggregation module 7022 and patient outcome analysis modules 7028. Different prioritization levels can result in particular responses from the cloud 7004 (corresponding to a level of urgency) such as escalation for an expedited response, special processing, exclusion from the aggregated medical data databases 7011, or other suitable responses. Moreover, if necessary, the cloud 7004 can transmit a request (e.g., a push message) through the hub application servers for additional data from corresponding surgical instruments 7012. The push message can result in a notification displayed on the corresponding hubs 7006 for requesting supporting or additional data. This push message may be required in situations in which the cloud detects a significant irregularity or outlier and the cloud cannot determine the cause of the irregularity. The central servers 7013 may be programmed to trigger this push message in certain significant circumstances, such as when data is determined to be different from an expected value beyond a predetermined threshold or when it appears security has been comprised, for example.

Additional example details for the various functions described are provided in the ensuing descriptions below. Each of the various descriptions may utilize the cloud architecture as described in FIGS. 11 and 12 as one example of hardware and software implementation.

FIG. 13 illustrates a block diagram of a computer-implemented adaptive surgical system 9060 that is configured to adaptively generate control program updates for modular devices 9050, in accordance with at least one aspect of the present disclosure. In some exemplifications, the surgical system may include a surgical hub 9000, multiple modular devices 9050 communicably coupled to the surgical hub 9000, and an analytics system 9100 communicably coupled to the surgical hub 9000. Although a single surgical hub 9000 may be depicted, it should be noted that the surgical system 9060 can include any number of surgical hubs 9000, which can be connected to form a network of surgical hubs 9000 that are communicably coupled to the analytics system 9010. In some exemplifications, the surgical hub 9000 may include a processor 9010 coupled to a memory 9020 for executing instructions stored thereon and a data relay interface 9030 through which data is transmitted to the analytics system 9100. In some exemplifications, the surgical hub 9000 further may include a user interface 9090 having an input device 9092 (e.g., a capacitive touchscreen or a keyboard) for receiving inputs from a user and an output device 9094 (e.g., a display screen) for providing outputs to a user. Outputs can include data from a query input by the user, suggestions for products or mixes of products to use in a given procedure, and/or instructions for actions to be carried out before, during, or after surgical procedures. The surgical hub 9000 further may include an interface 9040 for communicably coupling the modular devices 9050 to the surgical hub 9000. In one aspect, the interface 9040 may include a transceiver that is communicably connectable to the modular device 9050 via a wireless communication protocol. The modular devices 9050 can include, for example, surgical stapling and cutting instruments, electrosurgical instruments, ultrasonic instruments, insufflators, respirators, and display screens. In some exemplifications, the surgical hub 9000 can further be communicably coupled to one or more patient monitoring devices 9052, such as EKG monitors or BP monitors. In some exemplifications, the surgical hub 9000 can further be communicably coupled to one or more databases 9054 or external computer systems, such as an EMR database of the medical facility at which the surgical hub 9000 is located.

When the modular devices 9050 are connected to the surgical hub 9000, the surgical hub 9000 can sense or receive perioperative data from the modular devices 9050 and then associate the received perioperative data with surgical procedural outcome data. The perioperative data may indicate how the modular devices 9050 were controlled during the course of a surgical procedure. The procedural outcome data includes data associated with a result from the surgical procedure (or a step thereof), which can include whether the surgical procedure (or a step thereof) had a positive or negative outcome. For example, the outcome data could include whether a patient suffered from postoperative complications from a particular procedure or whether there was leakage (e.g., bleeding or air leakage) at a particular staple or incision line. The surgical hub 9000 can obtain the surgical procedural outcome data by receiving the data from an external source (e.g., from an EMR database 9054), by directly detecting the outcome (e.g., via one of the connected modular devices 9050), or inferring the occurrence of the outcomes through a situational awareness system. For example, data regarding postoperative complications could be retrieved from an EMR database 9054 and data regarding staple or incision line leakages could be directly detected or inferred by a situational awareness system. The surgical procedural outcome data can be inferred by a situational awareness system from data received from a variety of data sources, including the modular devices 9050 themselves, the patient monitoring device 9052, and the databases 9054 to which the surgical hub 9000 is connected.

The surgical hub 9000 can transmit the associated modular device 9050 data and outcome data to the analytics system 9100 for processing thereon. By transmitting both the perioperative data indicating how the modular devices 9050 are controlled and the procedural outcome data, the analytics system 9100 can correlate the different manners of controlling the modular devices 9050 with surgical outcomes for the particular procedure type. In some exemplifications, the analytics system 9100 may include a network of analytics servers 9070 that are configured to receive data from the surgical hubs 9000. Each of the analytics servers 9070 can include a memory and a processor coupled to the memory that is executing instructions stored thereon to analyze the received data. In some exemplifications, the analytics servers 9070 may be connected in a distributed computing architecture and/or utilize a cloud computing architecture. Based on this paired data, the analytics system 9100 can then learn optimal or preferred operating parameters for the various types of modular devices 9050, generate adjustments to the control programs of the modular devices 9050 in the field, and then transmit (or “push”) updates to the modular devices' 9050 control programs.

Additional detail regarding the computer-implemented interactive surgical system 9060, including the surgical hub 9000 and various modular devices 9050 connectable thereto, are described in connection with FIGS. 5-6.

FIG. 14 provides a surgical system 6500 in accordance with the present disclosure and may include a surgical instrument 6502 that can be in communication with a console 6522 or a portable device 6526 through a local area network 6518 or a cloud network 6520 via a wired or wireless connection. In various aspects, the console 6522 and the portable device 6526 may be any suitable computing device. The surgical instrument 6502 may include a handle 6504, an adapter 6508, and a loading unit 6514. The adapter 6508 releasably couples to the handle 6504 and the loading unit 6514 releasably couples to the adapter 6508 such that the adapter 6508 transmits a force from a drive shaft to the loading unit 6514. The adapter 6508 or the loading unit 6514 may include a force gauge (not explicitly shown) disposed therein to measure a force exerted on the loading unit 6514. The loading unit 6514 may include an end effector 6530 having a first jaw 6532 and a second jaw 6534. The loading unit 6514 may be an in-situ loaded or multi-firing loading unit (MFLU) that allows a clinician to fire a plurality of fasteners multiple times without requiring the loading unit 6514 to be removed from a surgical site to reload the loading unit 6514.

The first and second jaws 6532, 6534 may be configured to clamp tissue therebetween, fire fasteners through the clamped tissue, and sever the clamped tissue. The first jaw 6532 may be configured to fire at least one fastener a plurality of times, or may be configured to include a replaceable multi-fire fastener cartridge including a plurality of fasteners (e.g., staples, clips, etc.) that may be fired more than one time prior to being replaced. The second jaw 6534 may include an anvil that deforms or otherwise secures the fasteners about tissue as the fasteners are ejected from the multi-fire fastener cartridge.

The handle 6504 may include a motor that is coupled to the drive shaft to affect rotation of the drive shaft. The handle 6504 may include a control interface to selectively activate the motor. The control interface may include buttons, switches, levers, sliders, touchscreen, and any other suitable input mechanisms or user interfaces, which can be engaged by a clinician to activate the motor.

The control interface of the handle 6504 may be in communication with a controller 6528 of the handle 6504 to selectively activate the motor to affect rotation of the drive shafts. The controller 6528 may be disposed within the handle 6504 and is configured to receive input from the control interface and adapter data from the adapter 6508 or loading unit data from the loading unit 6514. The controller 6528 may analyze the input from the control interface and the data received from the adapter 6508 and/or loading unit 6514 to selectively activate the motor. The handle 6504 may also include a display that is viewable by a clinician during use of the handle 6504. The display may be configured to display portions of the adapter or loading unit data before, during, or after firing of the instrument 6502.

The adapter 6508 may include an adapter identification device 6510 disposed therein and the loading unit 6514 includes a loading unit identification device 6516 disposed therein. The adapter identification device 6510 may be in communication with the controller 6528, and the loading unit identification device 6516 may be in communication with the controller 6528. It will be appreciated that the loading unit identification device 6516 may be in communication with the adapter identification device 6510, which relays or passes communication from the loading unit identification device 6516 to the controller 6528.

The adapter 6508 may also include a plurality of sensors 6512 (one shown) disposed thereabout to detect various conditions of the adapter 6508 or of the environment (e.g., if the adapter 6508 is connected to a loading unit, if the adapter 6508 is connected to a handle, if the drive shafts are rotating, the torque of the drive shafts, the strain of the drive shafts, the temperature within the adapter 6508, a number of firings of the adapter 6508, a peak force of the adapter 6508 during firing, a total amount of force applied to the adapter 6508, a peak retraction force of the adapter 6508, a number of pauses of the adapter 6508 during firing, etc.). The plurality of sensors 6512 may provide an input to the adapter identification device 6510 in the form of data signals. The data signals of the plurality of sensors 6512 may be stored within, or be used to update the adapter data stored within, the adapter identification device 6510. The data signals of the plurality of sensors 6512 may be analog or digital. The plurality of sensors 6512 may include a force gauge to measure a force exerted on the loading unit 6514 during firing.

The handle 6504 and the adapter 6508 can be configured to interconnect the adapter identification device 6510 and the loading unit identification device 6516 with the controller 6528 via an electrical interface. The electrical interface may be a direct electrical interface (i.e., include electrical contacts that engage one another to transmit energy and signals therebetween). Additionally or alternatively, the electrical interface may be a non-contact electrical interface to wirelessly transmit energy and signals therebetween (e.g., inductively transfer). It is also contemplated that the adapter identification device 6510 and the controller 6528 may be in wireless communication with one another via a wireless connection separate from the electrical interface.

The handle 6504 may include a transmitter 6506 that is configured to transmit instrument data from the controller 6528 to other components of the system 6500 (e.g., the LAN 6518, the cloud 6520, the console 6522, or the portable device 6526). The transmitter 6506 also may receive data (e.g., cartridge data, loading unit data, or adapter data) from the other components of the system 6500. For example, the controller 6528 may transmit instrument data including a serial number of an attached adapter (e.g., adapter 6508) attached to the handle 6504, a serial number of a loading unit (e.g., loading unit 6514) attached to the adapter, and a serial number of a multi-fire fastener cartridge (e.g., multi-fire fastener cartridge), loaded into the loading unit, to the console 6528. Thereafter, the console 6522 may transmit data (e.g., cartridge data, loading unit data, or adapter data) associated with the attached cartridge, loading unit, and adapter, respectively, back to the controller 6528. The controller 6528 can display messages on the local instrument display or transmit the message, via transmitter 6506, to the console 6522 or the portable device 6526 to display the message on the display 6524 or portable device screen, respectively.

FIG. 15A illustrates an example flow for determining a mode of operation and operating in the determined mode. The computer-implemented interactive surgical system and/or components and/or subsystems of the computer-implemented interactive surgical system may be configured to be updated. Such updates may include the inclusions of features and benefits that were not available to the user before the update. These updates may be established by any method of hardware, firmware, and software updates suitable for introducing the feature to the user. For example, replaceable/swappable (e.g., hot swappable) hardware components, flashable firmware devices, and updatable software systems may be used to update computer-implemented interactive surgical system and/or components and/or subsystems of the computer-implemented interactive surgical system.

The updates may be conditioned on any suitable criterion or set of criteria. For example, an update may be conditioned on one or more hardware capabilities of the system, such as processing capability, bandwidth, resolution, and the like. For example, the update may be conditioned on one or more software aspects, such as a purchase of certain software code. For example, the update may be conditioned on a purchased service tier. The service tier may represent a feature and/or a set of features the user is entitled to use in connection with the computer-implemented interactive surgical system. The service tier may be determined by a license code, an e-commerce server authentication interaction, a hardware key, a username/password combination, a biometric authentication interaction, a public/private key exchange interaction, or the like.

At 10704, a system/device parameter may be identified. The system/device parameter may be any element or set of elements on which an update in conditioned. For example, the computer-implemented interactive surgical system may detect a certain bandwidth of communication between a modular device and a surgical hub. For example, the computer-implemented interactive surgical system may detect an indication of the purchase of certain service tier.

At 10708, a mode of operation may be determined based on the identified system/device parameter. This determination may be made by a process that maps system/device parameters to modes of operation. The process may be a manual and/or an automated process. The process may be the result of local computation and/or remote computation. For example, a client/server interaction may be used to determine the mode of operation based on the on the identified system/device parameter. For example, local software and/or locally embedded firmware may be used to determine the mode of operation based on the identified system/device parameter. For example, a hardware key, such as a secure microprocessor for example, may be used to determine the mode of operation based on the identified system/device parameter.

At 10710, operation may proceed in accordance with the determined mode of operation. For example, a system or device may proceed to operate in a default mode of operation. For example, a system or device may proceed to operate in an alternate mode of operation. The mode of operation may be directed by control hardware, firmware, and/or software already resident in the system or device. The mode of operation may be directed by control hardware, firmware, and/or software newly installed/updated.

FIG. 15B illustrates an example functional block diagram for changing a mode of operation. An upgradeable element 10714 may include an initialization component 10716. The initialization component 10716 may include any hardware, firmware, and/or software suitable determining a mode of operation. For example, the initialization component 10716 may be portion of a system or device start-up procedure. The initialization component 10716 may engage in an interaction to determine a mode of operation for the upgradeable element 10714. For example, the initialization component 10716 may interact with a user 10730, an external resource 10732, and/or a local resource 10718 for example. For example, the initialization component 10716 may receive a licensing key from the user 10730 to determine a mode of operation. The initialization component 10716 may query an external resource 10732, such as a server for example, with a serial number of the upgradable device 10714 to determine a mode of operation. For example, the initialization component 10716 may query a local resource 10718, such as a local query to determine an amount of available bandwidth and/or a local query of a hardware key for example, to determine a mode of operation.

The upgradeable element 10714 may include one or more operation components 10720, 10722, 10726, 10728 and an operational pointer 10724. The initialization component 10716 may direct the operational pointer 10724 to direct the operation of the upgradable element 10741 to the operation component 10720, 10722, 10726, 10728 that corresponds with the determined mode of operation. The initialization component 10716 may direct the operational pointer 10724 to direct the operation of the upgradable element to a default operation component 10720. For example, the default operation component 10720 may be selected on the condition of no other alternate mode of operation being determined. For example, the default operation component 10720 may be selected on the condition of a failure of the initialization component and/or interaction failure. The initialization component 10716 may direct the operational pointer 10724 to direct the operation of the upgradable element 10714 to a resident operation component 10722. For example, certain features may be resident in the upgradable component 10714 but require activation to be put into operation. The initialization component 10716 may direct the operational pointer 10724 to direct the operation of the upgradable element 10714 to install a new operation component 10728 and/or a new installed operation component 10726. For example, new software and/or firmware may be downloaded. The new software and or firmware may contain code to enable the features represented by the selected mode of operation. For example, a new hardware component may be installed to enable the selected mode of operation.

FIGS. 16A-D and FIGS. 17A-F depict various aspects of one example of a visualization system 2108 that may be incorporated into a surgical system. The visualization system 2108 may include an imaging control unit 2002 and a hand unit 2020. The imaging control unit 2002 may include one or more illumination sources, a power supply for the one or more illumination sources, one or more types of data communication interfaces (including USB, Ethernet, or wireless interfaces 2004), and one or more a video outputs 2006. The imaging control unit 2002 may further include an interface, such as a USB interface 2010, configured to transmit integrated video and image capture data to a USB enabled device. The imaging control unit 2002 may also include one or more computational components including, without limitation, a processor unit, a transitory memory unit, a non-transitory memory unit, an image processing unit, a bus structure to form data links among the computational components, and any interface (e.g. input and/or output) devices necessary to receive information from and transmit information to components not included in the imaging control unit. The non-transitory memory may further contain instructions that when executed by the processor unit, may perform any number of manipulations of data that may be received from the hand unit 2020 and/or computational devices not included in the imaging control unit.

The illumination sources may include a white light source 2012 and one or more laser light sources. The imaging control unit 2002 may include one or more optical and/or electrical interfaces for optical and/or electrical communication with the hand unit 2020. The one or more laser light sources may include, as non-limiting examples, any one or more of a red laser light source, a green laser light source, a blue laser light source, an infrared laser light source, and an ultraviolet laser light source. In some non-limiting examples, the red laser light source may source illumination having a peak wavelength that may range between 635 nm and 660 nm, inclusive. Non-limiting examples of a red laser peak wavelength may include about 635 nm, about 640 nm, about 645 nm, about 650 nm, about 655 nm, about 660 nm, or any value or range of values therebetween. In some non-limiting examples, the green laser light source may source illumination having a peak wavelength that may range between 520 nm and 532 nm, inclusive. Non-limiting examples of a green laser peak wavelength may include about 520 nm, about 522 nm, about 524 nm, about 526 nm, about 528 nm, about 530 nm, about 532 nm, or any value or range of values therebetween. In some non-limiting examples, the blue laser light source may source illumination having a peak wavelength that may range between 405 nm and 445 nm, inclusive. Non-limiting examples of a blue laser peak wavelength may include about 405 nm, about 410 nm, about 415 nm, about 420 nm, about 425 nm, about 430 nm, about 435 nm, about 440 nm, about 445 nm, or any value or range of values therebetween. In some non-limiting examples, the infrared laser light source may source illumination having a peak wavelength that may range between 750 nm and 3000 nm, inclusive. Non-limiting examples of an infrared laser peak wavelength may include about 750 nm, about 1000 nm, about 1250 nm, about 1500 nm, about 1750 nm, about 2000 nm, about 2250 nm, about 2500 nm, about 2750 nm, 3000 nm, or any value or range of values therebetween. In some non-limiting examples, the ultraviolet laser light source may source illumination having a peak wavelength that may range between 200 nm and 360 nm, inclusive. Non-limiting examples of an ultraviolet laser peak wavelength may include about 200 nm, about 220 nm, about 240 nm, about 260 nm, about 280 nm, about 300 nm, about 320 nm, about 340 nm, about 360 nm, or any value or range of values therebetween.

In one non-limiting aspect, the hand unit 2020 may include a body 2021, a camera scope cable 2015 attached to the body 2021, and an elongated camera probe 2024. The body 2021 of the hand unit 2020 may include hand unit control buttons 2022 or other controls to permit a health professional using the hand unit 2020 to control the operations of the hand unit 2020 or other components of the imaging control unit 2002, including, for example, the light sources. The camera scope cable 2015 may include one or more electrical conductors and one or more optical fibers. The camera scope cable 2015 may terminate with a camera head connector 2008 at a proximal end in which the camera head connector 2008 is configured to mate with the one or more optical and/or electrical interfaces of the imaging control unit 2002. The electrical conductors may supply power to the hand unit 2020, including the body 2021 and the elongated camera probe 2024, and/or to any electrical components internal to the hand unit 2020 including the body 2021 and/or elongated camera probe 2024. The electrical conductors may also serve to provide bi-directional data communication between any one or more components the hand unit 2020 and the imaging control unit 2002. The one or more optical fibers may conduct illumination from the one or more illumination sources in the imaging control unit 2002 through the hand unit body 2021 and to a distal end of the elongated camera probe 2024. In some non-limiting aspects, the one or more optical fibers may also conduct light reflected or refracted from the surgical site to one or more optical sensors disposed in the elongated camera probe 2024, the hand unit body 2021, and/or the imaging control unit 2002.

FIG. 16B (a top plan view) depicts in more detail some aspects of a hand unit 2020 of the visualization system 2108. The hand unit body 2021 may be constructed of a plastic material. The hand unit control buttons 2022 or other controls may have a rubber overmolding to protect the controls while permitting them to be manipulated by the surgeon. The camera scope cable 2015 may have optical fibers integrated with electrical conductors, and the camera scope cable 2015 may have a protective and flexible overcoating such as PVC. In some non-limiting examples, the camera scope cable 2015 may be about 10 ft. long to permit ease of use during a surgical procedure. The length of the camera scope cable 2015 may range from about 5 ft. to about 15 ft. Non-limiting examples of a length of the camera scope cable 2015 may be about 5 ft., about 6 ft., about 7 ft., about 8 ft., about 9 ft., about 10 ft., about 11 ft., about 12 ft., about 13 ft., about 14 ft., about 15 ft., or any length or range of lengths therebetween. The elongated camera probe 2024 may be fabricated from a rigid material such as stainless steel. In some aspects, the elongated camera probe 2024 may be joined with the hand unit body 2021 via a rotatable collar 2026. The rotatable collar 2026 may permit the elongated camera probe 2024 to be rotated with respect to the hand unit body 2021. In some aspects, the elongated camera probe 2024 may terminate at a distal end with a plastic window 2028 sealed with epoxy.

The side plan view of the hand unit, depicted in FIG. 16C illustrates that a light or image sensor 2030 maybe disposed at a distal end 2032 a of the elongated camera probe or within the hand unit body 2032 b. In some alternative aspects, the light or image sensor 2030 may be dispose with additional optical elements in the imaging control unit 2002. FIG. 16C further depicts an example of a light sensor 2030 comprising a CMOS image sensor 2034 disposed within a mount 2036 having a radius of about 4 mm. FIG. 16D illustrates aspects of the CMOS image sensor 2034, depicting the active area 2038 of the image sensor. Although the CMOS image sensor in FIG. 16C is depicted to be disposed within a mount 2036 having a radius of about 4 mm, it may be recognized that such a sensor and mount combination may be of any useful size to be disposed within the elongated camera probe 2024, the hand unit body 2021, or in the image control unit 2002. Some non-limiting examples of such alternative mounts may include a 5.5 mm mount 2136 a, a 4 mm mount 2136 b, a 2.7 mm mount 2136 c, and a 2 mm mount 2136 d. It may be recognized that the image sensor may also comprise a CCD image sensor. The CMOS or CCD sensor may comprise an array of individual light sensing elements (pixels).

FIGS. 17A-F depict various aspects of some examples of illumination sources and their control that may be incorporated into the visualization system 2108.

FIG. 17A illustrates an aspect of a laser illumination system having a plurality of laser bundles emitting a plurality of wavelengths of electromagnetic energy. As can be seen in the figure, the illumination system 2700 may comprise a red laser bundle 2720, a green laser bundle 2730, and a blue laser bundle 2740 that are all optically coupled together though fiber optics 2755. As can be seen in the figure, each of the laser bundles may have a corresponding light sensing element or electromagnetic sensor 2725, 2735, 2745 respectively, for sensing the output of the specific laser bundle or wavelength.

Additional disclosures regarding the laser illumination system depicted in FIG. 17A for use in a surgical visualization system 2108 may be found in U.S. Patent Application Publication No. 2014/0268860, tided CONTROLLING THE INTEGRAL LIGHT ENERGY OF A LASER PULSE filed on Mar. 15, 2014, which issued on Oct. 3, 2017 as U.S. Pat. No. 9,777,913, the contents thereof being incorporated by reference herein in its entirety and for all purposes.

FIG. 17B illustrates the operational cycles of a sensor used in rolling readout mode. It will be appreciated that the x direction corresponds to time and the diagonal lines 2202 indicate the activity of an internal pointer that reads out each frame of data, one line at time. The same pointer is responsible for resetting each row of pixels for the next exposure period. The net integration time for each row 2219 a-c is equivalent, but they are staggered in time with respect to one another due to the rolling reset and read process. Therefore, for any scenario in which adjacent frames are required to represent different constitutions of light, the only option for having each row be consistent is to pulse the light between the readout cycles 2230 a-c. More specifically, the maximum available period corresponds to the sum of the blanking time plus any time during which optical black or optically blind (OB) rows (2218, 2220) are serviced at the start or end of the frame.

FIG. 171B illustrates the operational cycles of a sensor used in rolling readout mode or during the sensor readout 2200. The frame readout may start at and may be represented by vertical line 2210. The read out period is represented by the diagonal or slanted line 2202. The sensor may be read out on a row by row basis, the top of the downwards slanted edge being the sensor top row 2212 and the bottom of the downwards slanted edge being the sensor bottom row 2214. The time between the last row readout and the next readout cycle may be called the blanking time 2216 a-d. It may be understood that the blanking time 2216 a-d may be the same between success readout cycles or it may differ between success readout cycles. It should be noted that some of the sensor pixel rows might be covered with a light shield (e.g., a metal coating or any other substantially black layer of another material type). These covered pixel rows may be referred to as optical black rows 2218 and 2220. Optical black rows 2218 and 2220 may be used as input for correction algorithms.

As shown in FIG. 17B, these optical black rows 2218 and 2220 may be located on the top of the pixel array or at the bottom of the pixel array or at the top and the bottom of the pixel array. In some aspects, it may be desirable to control the amount of electromagnetic radiation, e.g., light, that is exposed to a pixel, thereby integrated or accumulated by the pixel. It will be appreciated that photons are elementary particles of electromagnetic radiation. Photons are integrated, absorbed, or accumulated by each pixel and converted into an electrical charge or current. In some aspects, an electronic shutter or rolling shutter may be used to start the integration time (2219 a-c) by resetting the pixel. The light will then integrate until the next readout phase. In some aspects, the position of the electronic shutter can be moved between two readout cycles 2202 in order to control the pixel saturation for a given amount of light. In some alternative aspects lacking an electronic shutter, the integration time 2219 a-c of the incoming light may start during a first readout cycle 2202 and may end at the next readout cycle 2202, which also defines the start of the next integration. In some alternative aspects, the amount of light accumulated by each pixel may be controlled by a time during which light is pulsed 2230 a-d during the blanking times 2216 a-d. This ensures that all rows see the same light issued from the same light pulse 2230 a-c. In other words, each row will start its integration in a first dark environment 2231, which may be at the optical black back row 2220 of read out frame (m) for a maximum light pulse width, and will then receive a light strobe and will end its integration in a second dark environment 2232, which may be at the optical black front row 2218 of the next succeeding read out frame (m+1) for a maximum light pulse width. Thus, the image generated from the light pulse 2230 a-c will be solely available during frame (m+1) readout without any interference with frames (m) and (m+2).

It should be noted that the condition to have a light pulse 2230 a-c to be read out only in one frame and not interfere with neighboring frames is to have the given light pulse 2230 a-c firing during the blanking time 2216. Because the optical black rows 2218, 2220 are insensitive to light, the optical black back rows 2220 time of frame (m) and the optical black front rows 2218 time of frame (m+1) can be added to the blanking time 2216 to determine the maximum range of the firing time of the light pulse 2230.

In some aspects, FIG. 17B depicts an example of a timing diagram for sequential frame captures by a conventional CMOS sensor. Such a CMOS sensor may incorporate a Bayer pattern of color filters, as depicted in FIG. 17C. It is recognized that the Bayer pattern provides for greater luminance detail than chrominance. It may further be recognized that the sensor has a reduced spatial resolution since a total of 4 adjacent pixels are required to produce the color information for the aggregate spatial portion of the image. In an alternative approach, the color image may be constructed by rapidly strobing the visualized area at high speed with a variety of optical sources (either laser or light-emitting diodes) having different central optical wavelengths.

The optical strobing system may be under the control of the camera system, and may include a specially designed CMOS sensor with high speed readout. The principal benefit is that the sensor can accomplish the same spatial resolution with significantly fewer pixels compared with conventional Bayer or 3-sensor cameras. Therefore, the physical space occupied by the pixel array may be reduced. The actual pulse periods (2230 a-c) may differ within the repeating pattern, as illustrated in FIG. 17B. This is useful for, e.g., apportioning greater time to the components that require the greater light energy or those having the weaker sources. As long as the average captured frame rate is an integer multiple of the requisite final system frame rate, the data may simply be buffered in the signal processing chain as appropriate.

The facility to reduce the CMOS sensor chip-area to the extent allowed by combining all of these methods is particularly attractive for small diameter (about 3-10 mm) endoscopy. In particular, it allows for endoscope designs in which the sensor is located in the space-constrained distal end, thereby greatly reducing the complexity and cost of the optical section, while providing high definition video. A consequence of this approach is that to reconstruct each final, full color image, requires that data be fused from three separate snapshots in time. Any motion within the scene, relative to the optical frame of reference of the endoscope, will generally degrade the perceived resolution, since the edges of objects appear at slightly different locations within each captured component. In this disclosure, a means of diminishing this issue is described which exploits the fact that spatial resolution is much more important for luminance information, than for chrominance.

The basis of the approach is that, instead of firing monochromatic light during each frame, combinations of the three wavelengths are used to provide all of the luminance information within a single image. The chrominance information is derived from separate frames with, e.g., a repeating pattern such as Y-Cb-Y—Cr (FIG. 17D). While it is possible to provide pure luminance data by a shrewd choice of pulse ratios, the same is not true of chrominance.

In one aspect, as illustrated in FIG. 17D, an endoscopic system 2300 a may comprise a pixel array 2302 a having uniform pixels and the system 2300 a may be operated to receive Y (luminance pulse) 2304 a, Cb (ChromaBlue) 2306 a and Cr (ChromaRed) 2308 a pulses.

To complete a full color image requires that the two components of chrominance also be provided. However, the same algorithm that was applied for luminance cannot be directly applied for chrominance images since it is signed, as reflected in the fact that some of the RGB coefficients are negative. The solution to this is to add a degree of luminance of sufficient magnitude that all of the final pulse energies become positive. As long as the color fusion process in the ISP is aware of the composition of the chrominance frames, they can be decoded by subtracting the appropriate amount of luminance from a neighboring frame. The pulse energy proportions are given by:

Y=0.183·R+0.614·G+0.062·B

Cb=λ·Y−0.101·R−0.339·G+0.439·B

Cr=6·Y+0.439·R−0.399·G−0.040·B

λ≥0.399/0.614=0.552

δ≥0.399/0.614=0.650

It turns out that if the λ factor is equal to 0.552; both the red and the green components are exactly cancelled, in which case the Cb information can be provided with pure blue light. Similarly, setting δ=0.650 cancels out the blue and green components for Cr which becomes pure red. This particular example is illustrated in FIG. 17E, which also depicts λ and δ as integer multiples of

$\left( \frac{1}{2} \right)^{8}.$

This is a convenient approximation for the digital frame reconstruction.

In the case of the Y-Cb-Y—Cr pulsing scheme, the image data is already in the YCbCr space following the color fusion. Therefore, in this case it makes sense to perform luminance and chrominance-based operations up front, before converting back to linear RGB to perform the color correction etc.

The color fusion process is more straightforward than de-mosaic, which is necessitated by the Bayer pattern (see FIG. 17C), since there is no spatial interpolation. It does require buffering of frames though in order to have all of the necessary information available for each pixel. In one general aspect, data for the Y-Cb-Y—Cr pattern may be pipelined to yield one full color image per two raw captured images. This is accomplished by using each chrominance sample twice. In FIG. 17F the specific example of a 120 Hz frame capture rate providing 60 Hz final video is depicted.

Additional disclosures regarding the control of the laser components of an illumination system as depicted in FIGS. 17B-F for use in a surgical visualization system 108 may be found in U.S. Patent Application Publication No. 2014/0160318, titled YCBCR PULSED ILLUMINATION SCHEME IN A LIGHT DEFICIENT ENVIRONMENT, filed on Jul. 26, 2013, which issued on Dec. 6, 2016 as U.S. Pat. No. 9,516,239, and U.S. Patent Application Publication No. 2014/0160319, titled CONTINUOUS VIDEO IN A LIGHT DEFICIENT ENVIRONMENT, filed on Jul. 26, 2013, which issued on Aug. 22, 2017 as U.S. Pat. No. 9,743,016, the contents thereof being incorporated by reference herein in their entirety and for all purposes.

Subsurface Vascular Imaging

During a surgical procedure, a surgeon may be required to manipulate tissues to effect a desired medical outcome. The actions of the surgeon are limited by what is visually observable in the surgical site. Thus, the surgeon may not be aware, for example, of the disposition of vascular structures that underlie the tissues being manipulated during the procedure.

Since the surgeon is unable to visualize the vasculature beneath a surgical site, the surgeon may accidentally sever one or more critical blood vessels during the procedure.

Therefore, it is desirable to have a surgical visualization system that can acquire imaging data of the surgical site for presentation to a surgeon in which the presentation can include information related to the presence of vascular structures located beneath the surface of a surgical site.

Some aspects of the present disclosure further provide for a control circuit configured to control the illumination of a surgical site using one or more illumination sources such as laser light sources and to receive imaging data from one or more image sensors. In some aspects, the present disclosure provides for a non-transitory computer readable medium storing computer readable instructions that, when executed, cause a device to detect a blood vessel in a tissue and determine its depth below the surface of the tissue.

In some aspects, a surgical image acquisition system may include a plurality of illumination sources wherein each illumination source is configured to emit light having a specified central wavelength, a light sensor configured to receive a portion of the light reflected from a tissue sample when illuminated by the one or more of the plurality of illumination sources, and a computing system. The computing system may be configured to: receive data from the light sensor when the tissue sample is illuminated by each of the plurality of illumination sources; determine a depth location of a structure within the tissue sample based on the data received by the light sensor when the tissue sample is illuminated by each of the plurality of illumination sources, and calculate visualization data regarding the structure and the depth location of the structure. In some aspects, the visualization data may have a data format that may be used by a display system, and the structure may comprise one or more vascular tissues.

Vascular Imaging Using NIR Spectroscopy

In one aspect, a surgical image acquisition system may include an independent color cascade of illumination sources comprising visible light and light outside of the visible range to image one or more tissues within a surgical site at different times and at different depths. The surgical image acquisition system may further detect or calculate characteristics of the light reflected and/or refracted from the surgical site. The characteristics of the light may be used to provide a composite image of the tissue within the surgical site as well as provide an analysis of underlying tissue not directly visible at the surface of the surgical site. The surgical image acquisition system may determine tissue depth location without the need for separate measurement devices.

In one aspect, the characteristic of the light reflected and/or refracted from the surgical site may be an amount of absorbance of light at one or more wavelengths. Various chemical components of individual tissues may result in specific patterns of light absorption that are wavelength dependent.

In one aspect, the illumination sources may comprise a red laser source and a near infrared laser source, wherein the one or more tissues to be imaged may include vascular tissue such as veins or arteries. In some aspects, red laser sources (in the visible range) may be used to image some aspects of underlying vascular tissue based on spectroscopy in the visible red range. In some non-limiting examples, a red laser light source may source illumination having a peak wavelength that may range between 635 nm and 660 nm, inclusive. Non-limiting examples of a red laser peak wavelength may include about 635 nm, about 640 nm, about 645 nm, about 650 nm, about 655 nm, about 660 nm, or any value or range of values therebetween. In some other aspects, near infrared laser sources may be used to image underlying vascular tissue based on near infrared spectroscopy. In some non-limiting examples, a near infrared laser source may emit illumination have a wavelength that may range between 750-3000 nm, inclusive. Non-limiting examples of an infrared laser peak wavelength may include about 750 nm, about 1000 nm, about 1250 nm, about 1500 nm, about 1750 nm, about 2000 nm, about 2250 nm, about 2500 nm, about 2750 nm, 3000 nm, or any value or range of values therebetween. It may be recognized that underlying vascular tissue may be probed using a combination of red and infrared spectroscopy. In some examples, vascular tissue may be probed using a red laser source having a peak wavelength at about 660 nm and a near IR laser source having a peak wavelength at about 750 nm or at about 850 nm.

Near infrared spectroscopy (NIRS) is a non-invasive technique that allows determination of tissue oxygenation based on spectro-photometric quantitation of oxy- and deoxyhemoglobin within a tissue. In some aspects, NIRS can be used to image vascular tissue directly based on the difference in illumination absorbance between the vascular tissue and non-vascular tissue. Alternatively, vascular tissue can be indirectly visualized based on a difference of illumination absorbance of blood flow in the tissue before and after the application of physiological interventions, such as arterial and venous occlusions methods.

Instrumentation for near-IR (NIR) spectroscopy may be similar to instruments for the UV-visible and mid-IR ranges. Such spectroscopic instruments may include an illumination source, a detector, and a dispersive element to select a specific near-IR wavelength for illuminating the tissue sample. In some aspects, the source may comprise an incandescent light source or a quartz halogen light source. In some aspects, the detector may comprise semiconductor (for example, an InGaAs) photodiode or photo array. In some aspects, the dispersive element may comprise a prism or, more commonly, a diffraction grating. Fourier transform NIR instruments using an interferometer are also common, especially for wavelengths greater than about 1000 nm. Depending on the sample, the spectrum can be measured in either reflection or transmission mode.

FIG. 18 depicts schematically one example of instrumentation 2400 similar to instruments for the UV-visible and mid-IR ranges for NIR spectroscopy. A light source 2402 may emit a broad spectral range of illumination 2404 that may impinge upon a dispersive element 2406 (such as a prism or a diffraction grating). The dispersive element 2406 may operate to select a narrow wavelength portion 2408 of the light emitted by the broad spectrum light source 2402, and the selected portion 2408 of the light may illuminate the tissue 2410. The light reflected from the tissue 2412 may be directed to a detector 2416 (for example, by means of a dichroic mirror 2414) and the intensity of the reflected light 2412 may be recorded. The wavelength of the light illuminating the tissue 2410 may be selected by the dispersive element 2406. In some aspects, the tissue 2410 may be illuminated only by a single narrow wavelength portion 2408 selected by the dispersive element 2406 form the light source 2402. In other aspects, the tissue 2410 may be scanned with a variety of narrow wavelength portions 2408 selected by the dispersive element 2406. In this manner, a spectroscopic analysis of the tissue 2410 may be obtained over a range of NIR wavelengths.

FIG. 19 depicts schematically one example of instrumentation 2430 for determining NIRS based on Fourier transform infrared imaging. In FIG. 19, a laser source emitting 2432 light in the near IR range 2434 illuminates a tissue sample 2440. The light reflected 2436 by the tissue 2440 is reflected by a mirror, such as a dichroic mirror 2444, to a beam splitter 2446. The beam splitter 2446 directs one portion of the light 2448 reflected by the tissue 2440 to a stationary mirror 2450 and one portion of the light 2452 reflected 2436 by the tissue 2440 a moving mirror 2454. The moving mirror 2454 may oscillate in position based on an affixed piezoelectric transducer activated by a sinusoidal voltage having a voltage frequency. The position of the moving mirror 2454 in space corresponds to the frequency of the sinusoidal activation voltage of the piezoelectric transducer. The light reflected from the moving mirror and the stationary mirror may be recombined 2458 at the beam splitter 2446 and directed to a detector 2456. Computational components may receive the signal output of the detector 2456 and perform a Fourier transform (in time) of the received signal. Because the wavelength of the light received from the moving mirror 2454 varies in time with respect to the wavelength of the light received from the stationary mirror 2450, the time-based Fourier transform of the recombined light corresponds to a wavelength-based Fourier transform of the recombined light 2458. In this manner, a wavelength-based spectrum of the light reflected from the tissue 2440 may be determined and spectral characteristics of the light reflected 2436 from the tissue 2440 may be obtained. Changes in the absorbance of the illumination in spectral components from the light reflected from the tissue 2440 may thus indicate the presence or absence of tissue having specific light absorbing properties (such as hemoglobin).

An alternative to near infrared light to determine hemoglobin oxygenation would be the use of monochromatic red light to determine the red light absorbance characteristics of hemoglobin. The absorbance characteristics of red light having a central wavelength of about 660 nm by the hemoglobin may indicate if the hemoglobin is oxygenated (arterial blood) or deoxygenated (venous blood).

In some alternative surgical procedures, contrasting agents can be used to improve the data that is collected on oxygenation and tissue oxygen consumption. In one non-limiting example, NIRS techniques may be used in conjunction with a bolus injection of a near-IR contrast agent such as indocyanine green (ICG) which has a peak absorbance at about 800 nm. ICG has been used in some medical procedures to measure cerebral blood flow.

Vascular Imaging Using Laser Doppler Flowmetry

In one aspect, the characteristic of the light reflected and/or refracted from the surgical site may be a Doppler shift of the light wavelength from its illumination source.

Laser Doppler flowmetry may be used to visualize and characterized a flow of particles moving relative to an effectively stationary background. Thus, laser light scattered by moving particles, such as blood cells, may have a different wavelength than that of the original illuminating laser source. In contrast, laser light scattered by the effectively stationary background (for example, the vascular tissue) may have the same wavelength of that of the original illuminating laser source. The change in wavelength of the scattered light from the blood cells may reflect both the direction of the flow of the blood cells relative to the laser source as well as the blood cell velocity.

FIGS. 20A-C illustrate the change in wavelength of light scattered from blood cells that may be moving away from (FIG. 20A) or towards (FIG. 20C) the laser light source.

In each of FIGS. 20A-C, the original illuminating light 2502 is depicted having a relative central wavelength of 0. It may be observed from FIG. 20A that light scattered from blood cells moving away from the laser source 2504 has a wavelength shifted by some amount 2506 to a greater wavelength relative to that of the laser source (and is thus red shifted). It may also be observed from FIG. 20C that light scattered from blood cells moving towards from the laser source 2508 has a wavelength shifted by some amount 2510 to a shorter wavelength relative to that of the laser source (and is thus blue shifted). The amount of wavelength shift (for example 2506 or 2510) may be dependent on the velocity of the motion of the blood cells. In some aspects, an amount of a red shift (2506) of some blood cells may be about the same as the amount of blue shift (2510) of some other blood cells. Alternatively, an amount of a red shift (2506) of some blood cells may differ from the amount of blue shift (2510) of some other blood cells. Thus, the velocity of the blood cells flowing away from the laser source as depicted in FIG. 20A may be less than the velocity of the blood cells flowing towards the laser source as depicted in FIG. 26C based on the relative magnitude of the wavelength shifts (2506 and 2510). In contrast, and as depicted in FIG. 26B, light scattered from tissue not moving relative to the laser light source (for example blood vessels 2512 or non-vascular tissue 2514) may not demonstrate any change in wavelength.

FIG. 21 depicts an aspect of instrumentation 2530 that may be used to detect a Doppler shift in laser light scattered from portions of a tissue 2540. Light 2534 originating from a laser 2532 may pass through a beam splitter 2544. Some portion of the laser light 2536 may be transmitted by the beam splitter 2544 and may illuminate tissue 2540. Another portion of the laser light may be reflected 2546 by the beam splitter 2544 to impinge on a detector 2550. The light back-scattered 2542 by the tissue 254) may be directed by the beam splitter 2544 and also impinge on the detector 2550. The combination of the light 2534 originating from the laser 2532 with the light back-scattered 2542 by the tissue 2540 may result in an interference pattern detected by the detector 2550. The interference pattern received by the detector 2550 may include interference fringes resulting from the combination of the light 2534 originating from the laser 2532 and the Doppler shifted (and thus wavelength shifted) light back-scattered 2452 from the tissue 2540.

It may be recognized that hack-scattered light 2542 from the tissue 2540 may also include back scattered light from boundary layers within the tissue 2540 and/or wavelength-specific light absorption by material within the tissue 2540. As a result, the interference pattern observed at the detector 2550 may incorporate interference fringe features from these additional optical effects and may therefore confound the calculation of the Doppler shift unless properly analyzed.

FIG. 22 depicts some of these additional optical effects. It is well known that light traveling through a first optical medium having a first refractive index, n1, may be reflected at an interface with a second optical medium having a second refractive index, n2. The light transmitted through the second optical medium will have a transmission angle relative to the interface that differs from the angle of the incident light based on a difference between the refractive indices n1 and n2 (Snell's Law). FIG. 22 illustrates the effect of Snell's Law on light impinging on the surface of a multi-component tissue 2150, as may be presented in a surgical field. The multi-component tissue 2150 may be composed of an outer tissue layer 2152 having a refractive index n1 and a buried tissue, such as a blood vessel having a vessel wall 2156. The blood vessel wall 2156 may be characterized by a refractive index n2. Blood may flow within the lumen of the blood vessel 2160. In some aspects, it may be important during a surgical procedure to determine the position of the blood vessel 2160 below the surface 2154 of the outer tissue layer 2152 and to characterize the blood flow using Doppler shift techniques.

An incident laser light 2170 a may be used to probe for the blood vessel 2160 and may be directed on the top surface 2154 of the outer tissue layer 2152. A portion 2172 of the incident laser light 2170 a may be reflected at the top surface 2154. Another portion 2170 b of the incident laser light 2170 a may penetrate the outer tissue layer 2152. The reflected portion 2172 at the top surface 2154 of the outer tissue layer 2152 has the same path length of the incident light 2170 a, and therefore has the same wavelength and phase of the incident light 2170 a. How-ever, the portion 2170 b of light transmitted into the outer tissue layer 2152 will have a transmission angle that differs from the incidence angle of the light impinging on the tissue surface because the outer tissue layer 2152 has an index of refraction n1 that differs from the index of refraction of air.

If the portion of light transmitted through the outer tissue layer 2152 impinges on a second tissue surface 2158, for example of the blood vessel wall 2156, some portion 2174 a,b of light will be reflected back towards the source of the incident light 2170 a. The light thus reflected 2174 a at the interface between the outer tissue layer 2152 and the blood vessel wall 2156 will have the same wavelength as the incident light 2170 a, but will be phase shifted due to the change in the light path length. Projecting the light reflected 2174 a,b from the interface between the outer tissue layer 2152 and the blood vessel wall 2156 along with the incident light on the sensor, will produce an interference pattern based on the phase difference between the two light sources.

Further, a portion of the incident light 2170 c may be transmitted through the blood vessel wall 2156 and penetrate into the blood vessel lumen 2160. This portion of the incident light 2170 c may interact with the moving blood cells in the blood vessel lumen 2160 and may be reflected back 2176 a-c towards the source of the impinging light having a wavelength Doppler shifted according to the velocity of the blood cells, as disclosed above. The Doppler shifted light reflected 2176 a-c from the moving blood cells may be projected along with the incident light on the sensor, resulting in an interference pattern having a fringe pattern based on the wavelength difference between the two light sources.

In FIG. 22, a light path 2178 is presented of light impinging on the red blood cells in the blood vessel lumen 2160 if there are no changes in refractive index between the emitted light and the light reflected by the moving blood cells. In this example, only a Doppler shift in the reflected light wavelength can be detected. However, the light reflected by the blood cells (2176 a-c) may incorporate phase changes due to the variation in the tissue refractive indices in addition to the wavelength changes due to the Doppler Effect.

Thus, it may be understood that if the light sensor receives the incident light, the light reflected from one or more tissue interfaces (2172, and 2174 a,b) and the Doppler shifted light from the blood cells (2176 a-c), the interference pattern thus produced on the light sensor may include the effects due to the Doppler shift (change in wavelength) as well as the effects due to the change in refractive index within the tissue (change in phase). As a result, a Doppler analysis of the light reflected by the tissue sample may produce erroneous results if the effects due to changes in the refractive index within the sample are not compensated for.

FIG. 23 illustrates an example of the effects on a Doppler analysis of light that impinge 2250 on a tissue sample to determine the depth and location of an underlying blood vessel. If there is no intervening tissue between the blood vessel and the tissue surface, the interference pattern detected at the sensor may be due primarily to the change in wavelength reflected from the moving blood cells. As a result, a spectrum 2252 derived from the interference pattern may generally reflect only the Doppler shift of the blood cells. However, if there is intervening tissue between the blood vessel and the tissue surface, the interference pattern detected at the sensor may be due to a combination of the change in wavelength reflected from the moving blood cells and the phase shift due to the refractive index of the intervening tissue. A spectrum 2254 derived from such an interference pattern, may result in the calculation of the Doppler shift that is confounded due to the additional phase change in the reflected light. In some aspects, if information regarding the characteristics (thickness and refractive index) of the intervening tissue is known, the resulting spectrum 2256 may be corrected to provide a more accurate calculation of the change in wavelength.

It is recognized that the tissue penetration depth of light is dependent on the wavelength of the light used. Thus, the wavelength of the laser source light may be chosen to detect particle motion (such a blood cells) at a specific range of tissue depth.

FIGS. 24A-C depict schematically a means for detect moving particles such as blood cells at a variety of tissue depths based on the laser light wavelength. As illustrated in FIG. 24A, a laser source 2340 may direct an incident beam of laser light 2342 onto a surface 2344 of a surgical site. A blood vessel 2346 (such as a vein or artery) may be disposed within the tissue 2348 at some depth delta. from the tissue surface. The penetration depth 2350 of a laser into a tissue 2348 may be dependent at least in part on the laser wavelength. Thus, laser light having a wavelength in the red range of about 635 nm to about 660 nm, may penetrate the tissue 2351 a to a depth of about 1 mm. Laser light having a wavelength in the green range of about 520 nm to about 532 nm may penetrate the tissue 2351 b to a depth of about 2-3 mm. Laser light having a wavelength in the blue range of about 405 nm to about 445 nm may penetrate the tissue 2351 c to a depth of about 4 mm or greater. In the example depicted in FIGS. 30A-C, a blood vessel 2346 may be located at a depth .delta. of about 2-3 mm below the tissue surface. Red laser light will not penetrate to this depth and thus will not detect blood cells flowing within this vessel. However, both green and blue laser light can penetrate this depth. Therefore, scattered green and blue laser light from the blood cells within the blood vessel 2346 may demonstrate a Doppler shift in wavelength.

FIG. 24B illustrates how a Doppler shift 2355 in the wavelength of reflected laser light may appear. The emitted light (or laser source light 2342) impinging on a tissue surface 2344 may have a central wavelength 2352. For example, light from a green laser may have a central wavelength 2352 within a range of about 520 nm to about 532 nm. The reflected green light may have a central wavelength 2354 shifted to a longer wavelength (red shifted) if the light was reflected from a particle such as a red blood cell that is moving away from the detector. The difference between the central wavelength 2352 of the emitted laser light and the central wavelength 2354 of the emitted laser light comprises the Doppler shift 2355.

As disclosed above with respect to FIGS. 22 and 23, laser light reflected from structures within a tissue 2348 may also show a phase shift in the reflected light due to changes in the index of refraction arising from changes in tissue structure or composition. The emitted light (or laser source light 2342) impinging on a tissue surface 2344 may have a first phase characteristic 2356. The reflected laser light may have a second phase characteristic 2358. It may be recognized that blue laser light that can penetrate tissue to a depth of about 4 mm or greater 2351 c may encounter a greater variety of tissue structures than red laser light (about 1 mm 2351 a) or green laser light (about 2-3 mm 2351 b). Consequently, as illustrated in FIG. 30C, the phase shift 2358 of reflected blue laser light may be significant at least due to the depth of penetration.

FIG. 24D illustrates aspects of illuminating tissue by red 2360 a, green 2360 b and blue 2360 c laser light in a sequential manner. In some aspects, a tissue may be probed by red 2360 a, green 2360 b and blue 2360 c laser illumination in a sequential manner. In some alternative examples, one or more combinations of red 2360 a, green 2360 b, and blue 2360 c laser light, as depicted in FIG. 17D-F and disclosed above, may be used to illuminate the tissue according to a defined illumination sequence. 24D illustrates the effect of such illumination on a CMOS imaging sensor 2362 a-d over time. Thus, at a first time t.sub.1, the CMOS sensor 2362 a may be illuminated by the red 2360 a laser. At a second time t.sub.2 the CMOS sensor 2362 b may be illuminated by the green 2360 b laser. At a third time t.sub.3, the CMOS sensor 2362 c may be illuminated by the blue 2360 c laser. The illumination cycle may then be repeated starting at a fourth time t.sub.4 in which the CMOS sensor 2362 d may be illuminated by the red 2360 a lase again. It may be recognized that sequential illumination of the tissue by laser illumination at differing wavelengths may permit a Doppler analysis at varying tissue depths over time. Although red 2360 a, green 2360 b and blue 2360 c laser sources may be used to illuminate the surgical site, it may be recognized that other wavelengths outside of visible light (such as in the infrared or ultraviolet regions) may be used to illuminate the surgical site for Doppler analysis.

FIG. 25 illustrates an example of a use of Doppler imaging to detect the present of blood vessels not otherwise viewable at a surgical site 2600. In FIG. 25, a surgeon may wish to excise a tumor 2602 found in the right superior posterior lobe 2604 of a lung. Because the lungs are highly vascular, care must be taken to identify only those blood vessels associate with the tumor and to seal only those vessels without compromising the blood flow to the non-affected portions of the lung. In FIG. 25, the surgeon has identified the margin 2606 of the tumor 2604. The surgeon may then cut an initial dissected area 2608 in the margin region 2606, and exposed blood vessels 2610 may be observed for cutting and sealing. The Doppler imaging detector 2620 may be used to locate and identify blood vessels not observable 2612 in the dissected area. An imaging system may receive data from the Doppler imaging detector 2620 for analysis and display of the data obtained from the surgical site 2600. In some aspects, the imaging system may include a display to illustrate the surgical site 2600 including a visible image of the surgical site 2600 along with an image overlay of the hidden blood vessels 2612 on the image of the surgical site 2600.

In the scenario disclosed above regarding FIG. 25, a surgeon wishes to sever blood vessels that supply oxygen and nutrients to a tumor while sparing blood vessels associated with non-cancerous tissue. Additionally, the blood vessels may be disposed at different depths in or around the surgical site 2600. The surgeon must therefore identify the position (depth) of the blood vessels as well as determine if they are appropriate for resection. FIG. 26 illustrates one method for identifying deep blood vessels based on a Doppler shift of light from blood cells flowing therethrough. As disclosed above, red laser light has a penetration depth of about 1 mm and green laser light has a penetration depth of about 2-3 mm. However, a blood vessel having a below-surface depth of 4 mm or more will be outside the penetration depths at these wavelengths. Blue laser light, however, can detect such blood vessels based on their blood flow.

FIG. 26 depicts the Doppler shift of laser light reflected from a blood vessel at a specific depth below a surgical site. The site may be illuminated by red laser light, green laser light, and blue laser light. The central wavelength 2630 of the illuminating light may be normalized to a relative central 3631. If the blood vessel lies at a depth of 4 or more mm below the surface of the surgical site, neither the red laser light nor the green laser light will be reflected by the blood vessel. Consequently, the central wavelength 2632 of the reflected red light and the central wavelength 2634 of the reflected green light will not differ much from the central wavelength 2630 of the illuminating red light or green light, respectively. However, if the site is illuminated by blue laser light, the central wavelength 2638 of the reflected blue light 2636 will differ from the central wavelength 2630 of the illuminating blue light. In some instances, the amplitude of the reflected blue light 2636 may also be significantly reduced from the amplitude of the illuminating blue light. A surgeon may thus determine the presence of a deep lying blood vessel along with its approximate depth, and thereby avoiding the deep blood vessel during surface tissue dissection.

FIGS. 27 and 28 illustrates schematically the use of laser sources having differing central wavelengths (colors) for determining the approximate depth of a blood vessel beneath the surface of a surgical site. FIG. 27 depicts a first surgical site 2650 having a surface 2654 and a blood vessel 2656 disposed below the surface 2654. In one method, the blood vessel 2656 may be identified based on a Doppler shift of light impinging on the flow 2658 of blood cells within the blood vessel 2656. The surgical site 2650 may be illuminated by light from a number of lasers 2670, 2676, 2682, each laser being characterized by emitting light at one of several different central wavelengths. As noted above, illumination by a red laser 2670 can only penetrate tissue by about 1 mm. Thus, if the blood vessel 2656 was located at a depth of less than 1 mm 2672 below the surface 2654, the red laser illumination would be reflected 2674 and a Doppler shift of the reflected red illumination 2674 may be determined. Further, as noted above, illumination by a green laser 2676 can only penetrate tissue by about 2-3 mm. If the blood vessel 2656 was located at a depth of about 2-3 mm 2678 below the surface 2654, the green laser illumination would be reflected 2680 while the red laser illumination 2670 would not, and a Doppler shift of the reflected green illumination 2680 may be determined. However, as depicted in FIG. 27, the blood vessel 2656 is located at a depth of about 4 mm 2684 below the surface 2654. Therefore, neither the red laser illumination 2670 nor the green laser illumination 2676 would be reflected. Instead, only the blue laser illumination would be reflected 2686 and a Doppler shift of the reflected blue illumination 2686 may be determined.

In contrast to the blood vessel 2656 depicted in FIG. 27, the blood vessel 2656′ depicted in FIG. 28 is located closer to the surface of the tissue at the surgical site. Blood vessel 2656′ may also be distinguished from blood vessel 2656 in that blood vessel 2656′ is illustrated to have a much thicker wall 2657. Thus, blood vessel 2656′ may be an example of an artery while blood vessel 2656 may be an example of a vein because arterial walls are known to be thicker than venous walls. In some examples, arterial walls may have a thickness of about 1.3 mm. As disclosed above, red laser illumination 2670′ can penetrate tissue to a depth of about 1 mm 2672′. Thus, even if a blood vessel 2656′ is exposed at a surgical site (see 2610 at FIG. 25), red laser light that is reflected 2674′ from the surface of the blood vessel 2656′, may not be able to visualize blood flow 2658′ within the blood vessel 2656′ under a Doppler analysis due to the thickness of the blood vessel wall 2657. However, as disclosed above, green laser light impinging 2676′ on the surface of a tissue may penetrate to a depth of about 2-3 mm 2678′. Further, blue laser light impinging 2682′ on the surface of a tissue may penetrate to a depth of about 4 mm 2684′. Consequently, green laser light may be reflected 2680′ from the blood cells flowing 2658′ within the blood vessel 2656′ and blue laser light may be reflected 2686′ from the blood cells flowing 2658′ within the blood vessel 2656′. As a result, a Doppler analysis of the reflected green light 2680′ and reflected blue light 2686′ may provide information regarding blood flow in near-surface blood vessel, especially the approximate depth of the blood vessel.

As disclosed above, the depth of blood vessels below the surgical site may be probed based on wavelength-dependent Doppler imaging. The amount of blood flow through such a blood vessel may also be determined by speckle contrast (interference) analysis. Doppler shift may indicate a moving particle with respect to a stationary light source. As disclosed above, the Doppler wavelength shift may be an indication of the velocity of the particle motion. Individual particles such as blood cells may not be separately observable. However, the velocity of each blood cell will produce a proportional Doppler shift. An interference pattern may be generated by the combination of the light back-scattered from multiple blood cells due to the differences in the Doppler shift of the back-scattered light from each of the blood cells. The interference pattern may be an indication of the number density of blood cells within a visualization frame. The interference pattern may be termed speckle contrast. Speckle contrast analysis may be calculated using a full frame 300.times.300 CMOS imaging array, and the speckle contrast may be directly related to the amount of moving particles (for example blood cells) interacting with the laser light over a given exposure period.

A CMOS image sensor may be coupled to a digital signal processor (DSP). Each pixel of the sensor may be multiplexed and digitized. The Doppler shift in the light may be analyzed by looking at the source laser light in comparison to the Doppler shifted light. A greater Doppler shift and speckle may be related to a greater number of blood cells and their velocity in the blood vessel.

FIG. 29 depicts an aspect of a composite visual display 2800 that may be presented a surgeon during a surgical procedure. The composite visual display 2800 may be constructed by overlaying a white light image 2830 of the surgical site with a Doppler analysis image 2850.

In some aspects, the white light image 2830 may portray the surgical site 2832, one or more surgical incisions 2834, and the tissue 2836 readily visible within the surgical incision 2834. The white light image 2830 may be generated by illuminating 2840 the surgical site 2832 with a white light source 2838 and receiving the reflected white light 2842 by an optical detector. Although a white light source 2838 may be used to illuminate the surface of the surgical site, in one aspect, the surface of the surgical site may be visualized using appropriate combinations of red 2854, green 2856, and blue 2858 laser light as disclosed above with respect to FIGS. 17C-F.

In some aspects, the Doppler analysis image 2850 may include blood vessel depth information along with blood flow information 2852 (from speckle analysis). As disclosed above, blood vessel depth and blood flow velocity may be obtained by illuminating the surgical site with laser light of multiple wavelengths, and determining the blood vessel depth and blood flow based on the known penetration depth of the light of a particular wavelength. In general, the surgical site 2832 may be illuminated by light emitted by one or more lasers such as a red leaser 2854, a green laser 2856, and a blue laser 2858. A CMOS detector 2872 may receive the light reflected back (2862, 2866, 2870) from the surgical site 2832 and its surrounding tissue. The Doppler analysis image 2850 may be constructed 2874 based on an analysis of the multiple pixel data from the CMOS detector 2872.

In one aspect, a red laser 2854 may emit red laser illumination 2860 on the surgical site 2832 and the reflected light 2862 may reveal surface or minimally subsurface structures. In one aspect, a green laser 2856 may emit green laser illumination 2864 on the surgical site 2832 and the reflected light 2866 may reveal deeper subsurface characteristics. In another aspect, a blue laser 2858 may emit blue laser illumination 2868 on the surgical site 2832 and the reflected light 2870 may reveal, for example, blood flow within deeper vascular structures. In addition, the speckle contrast analysis my present the surgeon with information regarding the amount and velocity of blood flow through the deeper vascular structures.

Although not depicted in FIG. 29, it may be understood that the imaging system may also illuminate the surgical site with light outside of the visible range. Such light may include infra red light and ultraviolet light. In some aspects, sources of the infra red light or ultraviolet light may include broad-band wavelength sources (such as a tungsten source, a tungsten-halogen source, or a deuterium source). In some other aspects, the sources of the infra red or ultraviolet light may include narrow-band wavelength sources (IR diode lasers, UV gas lasers or dye lasers).

FIG. 30 is a flow chart 2900 of a method for determining a depth of a surface feature in a piece of tissue. An image acquisition system may illuminate 2910 a tissue with a first light beam having a first central frequency and receive 2912 a first reflected light from the tissue illuminated by the first light beam. The image acquisition system may then calculate 2914 a first Doppler shift based on the first light beam and the first reflected light. The image acquisition system may then illuminate 2916 the tissue with a second light beam having a second central frequency and receive 2918 a second reflected light from the tissue illuminated by the second light beam. The image acquisition system may then calculate 2920 a second Doppler shift based on the second light beam and the second reflected light. The image acquisition system may then calculate 2922 a depth of a tissue feature based at least in part on the first central wavelength, the first Doppler shift, the second central wavelength, and the second Doppler shift. In some aspects, the tissue features may include the presence of moving particles, such as blood cells moving within a blood vessel, and a direction and velocity of flow of the moving particles. It may be understood that the method may be extended to include illumination of the tissue by any one or more additional light beams. Further, the system may calculate an image comprising a combination of an image of the tissue surface and an image of the structure disposed within the tissue.

In some aspects, multiple visual displays may be used. For example, a 3D display may provide a composite image displaying the combined white light (or an appropriate combination of red, green, and blue laser light) and laser Doppler image. Additional displays may provide only the white light display or a displaying showing a composite white light display and an NIRS display to visualize only the blood oxygenation response of the tissue. However, the NIRS display may not be required every cycle allowing for response of tissue.

Subsurface Tissue Characterization Using Multispectral OCT

During a surgical procedure, the surgeon may employ “smart” surgical devices for the manipulation of tissue. Such devices may be considered “smart” in that they include automated features to direct, control, and/or vary the actions of the devices-based parameters relevant to their uses. The parameters may include the type and/or composition of the tissue being manipulated. If the type and/or composition of the tissue being manipulated is unknown, the actions of the smart devices may be inappropriate for the tissue being manipulated. As a result, tissues may be damaged or the manipulation of the tissue may be ineffective due to inappropriate settings of the smart device.

The surgeon may manually attempt to vary the parameters of the smart device in a trial-and-error manner, resulting in an inefficient and lengthy surgical procedure.

Therefore, it is desirable to have a surgical visualization system that can probe tissue structures underlying a surgical site to determine their structural and compositional characteristics, and to provide such data to smart surgical instruments being used in a surgical procedure.

Some aspects of the present disclosure further provide for a control circuit configured to control the illumination of a surgical site using one or more illumination sources such as laser light sources and to receive imaging data from one or more image sensors. In some aspects, the present disclosure provides for a non-transitory computer readable medium storing computer readable instructions that, when executed, cause a device to characterize structures below the surface at a surgical site and determine the depth of the structures below the surface of the tissue.

In some aspects, a surgical image acquisition system may comprise a plurality of illumination sources wherein each illumination source is configured to emit light having a specified central wavelength, a light sensor configured to receive a portion of the light reflected from a tissue sample when illuminated by the one or more of the plurality of illumination sources, and a computing system. The computing system may be configured to receive data from the light sensor when the tissue sample is illuminated by each of the plurality of illumination sources, calculate structural data related to a characteristic of a structure within the tissue sample based on the data received by the light sensor when the tissue sample is illuminated by each of the illumination sources, and transmit the structural data related to the characteristic of the structure to be received by a smart surgical device. In some aspects, the characteristic of the structure is a surface characteristic or a structure composition.

In one aspect, a surgical system may include multiple laser light sources and may receive laser light reflected from a tissue. The light reflected from the tissue may be used by the system to calculate surface characteristics of components disposed within the tissue. The characteristics of the components disposed within the tissue may include a composition of the components and/or a metric related to surface irregularities of the components.

In one aspect, the surgical system may transmit data related to the composition of the components and/or metrics related to surface irregularities of the components to a second instrument to be used on the tissue to modify the control parameters of the second instrument.

In some aspects, the second device may be an advanced energy device and the modifications of the control parameters may include a clamp pressure, an operational power level, an operational frequency, and a transducer signal amplitude.

As disclosed above, blood vessels may be detected under the surface of a surgical site base on the Doppler shift in light reflected by the blood cells moving within the blood vessels.

Laser Doppler flowmetry may be used to visualize and characterized a flow of particles moving relative to an effectively stationary background. Thus, laser light scattered by moving particles, such as blood cells, may have a different wavelength than that of the original illuminating laser source. In contrast, laser light scattered by the effectively stationary background (for example, the vascular tissue) may have the same wavelength of that of the original illuminating laser source. The change in wavelength of the scattered light from the blood cells may reflect both the direction of the flow of the blood cells relative to the laser source as well as the blood cell velocity. As previously disclosed, FIGS. 20A-C illustrate the change in wavelength of light scattered from blood cells that may be moving away from (FIG. 20A) or towards (FIG. 20C) the laser light source.

In each of FIGS. 20A-C, the original illuminating light 2502 is depicted having a relative central wavelength of 0. It may be observed from FIG. 20A that light scattered from blood cells moving away from the laser source 2504 has a wavelength shifted by some amount 2506 to a greater wavelength relative to that of the laser source (and is thus red shifted). It may also be observed from FIG. 18C that light scattered from blood cells moving towards from the laser source 2508 has a wavelength shifted by some amount 2510 to a shorter wavelength relative to that of the laser source (and is thus blue shifted). The amount of wavelength shift (for example 2506 or 2510) may be dependent on the velocity of the motion of the blood cells. In some aspects, an amount of a red shift (2506) of some blood cells may be about the same as the amount of blue shift (2510) of some other blood cells. Alternatively, an amount of a red shift (2506) of some blood cells may differ from the amount of blue shift (2510) of some other blood cells Thus, the velocity of the blood cells flowing away from the laser source as depicted in FIG. 24A may be less than the velocity of the blood cells flowing towards the laser source as depicted in FIG. 20C based on the relative magnitude of the wavelength shifts (2506 and 2510). In contrast, and as depicted in FIG. 20B, light scattered from tissue not moving relative to the laser light source (for example blood vessels 2512 or non-vascular tissue 2514) may not demonstrate any change in wavelength.

As previously disclosed, FIG. 21 depicts an aspect of instrumentation 2530 that may be used to detect a Doppler shift in laser light scattered from portions of a tissue 2540. Light 2534 originating from a laser 2532 may pass through a beam splitter 2544. Some portion of the laser light 2536 may be transmitted by the beam splitter 2544 and may illuminate tissue 2540. Another portion of the laser light may be reflected 2546 by the beam splitter 2544 to impinge on a detector 2550. The light back-scattered 2542 by the tissue 2540 may be directed by the beam splitter 2544 and also impinge on the detector 2550. The combination of the light 2534 originating from the laser 2532 with the light back-scattered 2542 by the tissue 2540 may result in an interference pattern detected by the detector 2550. The interference pattern received by the detector 2550 may include interference fringes resulting from the combination of the light 2534 originating from the laser 2532 and the Doppler shifted (and thus wavelength shifted) light back-scattered 2452 from the tissue 2540.

It may be recognized that back-scattered light 2542 from the tissue 2540 may also include back scattered light from boundary layers within the tissue 2540 and/or wavelength-specific light absorption by maternal within the tissue 2540. As a result, the interference pattern observed at the detector 2550 may incorporate interference fringe features from these additional optical effects and may therefore confound the calculation of the Doppler shift unless properly analyzed.

It may be recognized that light reflected from the tissue may also include back scattered light from boundary layers within the tissue and/or wavelength-specific light absorption by material within the tissue. As a result, the interference pattern observed at the detector may incorporate fringe features that may confound the calculation of the Doppler shift unless properly analyzed.

As previously disclosed, FIG. 22 depicts some of these additional optical effects. It is well known that light traveling through a first optical medium having a first refractive index, n1, may be reflected at an interface with a second optical medium having a second refractive index, n2. The light transmitted through the second optical medium will have a transmission angle relative to the interface that differs from the angle of the incident light based on a difference between the refractive indices n1 and n2 (Snell's Law). FIG. 20 illustrates the effect of Snell's Law on light impinging on the surface of a multi-component tissue 2150, as may be presented in a surgical field. The multi-component tissue 2150 may be composed of an outer tissue layer 2152 having a refractive index n1 and a buried tissue, such as a blood vessel having a vessel wall 2156. The blood vessel wall 2156 may be characterized by a refractive index n2. Blood may flow within the lumen of the blood vessel 2160. In some aspects, it may be important during a surgical procedure to determine the position of the blood vessel 2160 below the surface 2154 of the outer tissue layer 2152 and to characterize the blood flow using Doppler shift techniques.

An incident laser light 2170 a may be used to probe for the blood vessel 2160 and may be directed on the top surface 2154 of the outer tissue layer 2152. A portion 2172 of the incident laser light 2170 a may be reflected at the top surface 2154. Another portion 2170 b of the incident laser light 2170 ra may penetrate the outer tissue layer 2152. The reflected portion 2172 at the top surface 2154 of the outer tissue layer 2152 has the same path length of the incident light 2170 a, and therefore has the same wavelength and phase of the incident light 2170 a. However, the portion 2170 b of light transmitted into the outer tissue layer 2152 will have a transmission angle that differs from the incidence angle of the light impinging on the tissue surface because the outer tissue layer 2152 has an index of refraction n1 that differs from the index of refraction of air.

If the portion of light transmitted through the outer tissue layer 2152 impinges on a second tissue surface 2158, for example of the blood vessel wall 2156, some portion 2174 a,b of light will be reflected back towards the source of the incident light 2170 a. The light thus reflected 2174 a at the interface between the outer tissue layer 2152 and the blood vessel wall 2156 will have the same wavelength as the incident light 2170 a, but will be phase shifted due to the change in the light path length. Projecting the light reflected 2174 a,b from the interface between the outer tissue layer 2152 and the blood vessel wall 2156 along with the incident light on the sensor, will produce an interference pattern based on the phase difference between the two light sources.

Further, a portion of the incident light 2170 c may be transmitted through the blood vessel wall 2156 and penetrate into the blood vessel lumen 2160. This portion of the incident light 2170 c may interact with the moving blood cells in the blood vessel lumen 2160 and may be reflected back 2176 a-c towards the source of the impinging light having a wavelength Doppler shifted according to the velocity of the blood cells, as disclosed above. The Doppler shifted light reflected 2176 a-c from the moving blood cells may be projected along with the incident light on the sensor, resulting in an interference pattern having a fringe pattern based on the wavelength difference between the two light sources.

In FIG. 22, a light path 2178 is presented of light impinging on the red blood cells in the blood vessel lumen 216) if there are no changes in refractive index between the emitted light and the light reflected by the moving blood cells. In this example, only a Doppler shift in the reflected light wavelength can be detected. However, the light reflected by the blood cells (2176 a-c) may incorporate phase changes due to the variation in the tissue refractive indices in addition to the wavelength changes due to the Doppler Effect.

Thus, it may be understood that if the light sensor receives the incident light, the light reflected from one or more tissue interfaces (2172, and 2174 a,b) and the Doppler shifted light from the blood cells (2176 a-c), the interference pattern thus produced on the light sensor may include the effects due to the Doppler shift (change in wavelength) as well as the effects due to the change in refractive index within the tissue (change in phase). As a result, a Doppler analysis of the light reflected by the tissue sample may produce erroneous results if the effects due to changes in the refractive index within the sample are not compensated for.

As previously disclosed, FIG. 23 illustrates an example of the effects on a Doppler analysis of light that impinge 2250 on a tissue sample to determine the depth and location of an underlying blood vessel. If there is no intervening tissue between the blood vessel and the tissue surface, the interference pattern detected at the sensor may be due primarily to the change in wavelength reflected from the moving blood cells. As a result, a spectrum 2252 derived from the interference pattern may generally reflect only the Doppler shift of the blood cells. However, if there is intervening tissue between the blood vessel and the tissue surface, the interference pattern detected at the sensor may be due to a combination of the change in wavelength reflected from the moving blood cells and the phase shift due to the refractive index of the intervening tissue. A spectrum 2254 derived from such an interference pattern, may result in the calculation of the Doppler shift that is confounded due to the additional phase change in the reflected light. In some aspects, if information regarding the characteristics (thickness and refractive index) of the intervening tissue is known, the resulting spectrum 2256 may be corrected to provide a more accurate calculation of the change in wavelength.

It may be recognized that the phase shift in the reflected light from a tissue may provide additional information regarding underlying tissue structures, regardless of Doppler effects.

A surgical visualization systems using the imaging technologies disclosed herein may benefit from ultrahigh sampling and display frequencies. Sampling rates may be associated with the capabilities of the underlying device performing the sampling. A general-purpose computing system with software may be associated with a first range of achievable sampling rates. A pure-hardware implementation (e.g., a dedicated application specific integrated circuit, ASIC) may be associated with a second range of achievable sampling rates. The second range, associated with the pure-hardware implementation, will generally be higher (e.g., much higher) than the first range, associated with general-purpose computing software implementation.

A surgical visualization systems using the imaging technologies disclosed herein may benefit from adaptable and/or updatable imaging algorithms (such as transforms and imaging processing for example). A general-purpose computing system with software may be associated with high degree of adaptability and/or upgradability. A pure-hardware implementation (e.g., a dedicated application specific integrated circuit, ASIC) may be associated with generally lower degree of adaptability and/or upgradability than that of general-purpose computing system with software. This may be due, in part, to the general ease at which software may be adapted and/or updated (which may include compiling and loading different software and/or updating modular components) compared to pure-hardware implementations (in which new hardware components are designed, built, added and/or swapped, physically).

A surgical visualization system using the imaging technologies disclosed herein may benefit from solutions that balance the higher sampling rates, associated with hardware-based implementations, with the adaptability and/or updatability of software systems. Such a surgical visualization systems may employ a mix of hardware and software solutions. For example, a surgical visualization system may employ various hardware-implemented transforms with a software selector. A surgical visualization system may also employ a field programmable gate array (FPGA). An FPGA may include a hardware device that may include one or more logic elements. These logic elements may be configured by a bitstream to implement various functions. For example, the logic elements may be configured to perform certain individual logic functions and configured to perform them with a certain order and interconnection. Once configured, the FPGA may perform its function using the hardware logic elements without further configuration. Also once configured, the FPGA may be reconfigured with a different bitstream to implement a different function. And similarly, once reconfigured, the FPGA may perform this different function using the hardware logic elements.

FIG. 31 illustrates an example surgical visualization system 10000. The surgical visualization system 10000 may be used to analyze at least a portion of a surgical field. For example, the surgical visualization system 10000 may be used to analyze tissue 10002 within the at least a portion of the surgical field. The surgical visualization system 10000 may include a field programmable gate array (FPGA) 10004, a processor (for example, a processor 10006 local to the FPGA 10004, a memory 10008, a laser-light illumination source 10010, a light sensor 10012, a display 10014, and/or a processor 10016 remote to the FGPA. The surgical visualization system 10000 may include components and functionality described in connection with FIGS. 16A-D for example.

The system 10000 may use an FPGA 10004 to convert the reflected laser light thru a transform of frequency to identify a Doppler shift, for example, of the light to determine moving particles. This transformed data may be displayed (e.g., displayed in real-time). It may be displayed, for example, as a graphic and/or metric 10020, representing the number of moving particles each second. The system 10000 may include communication between the processor 10006 local to the FPGA 10004 and the processor 10016 remote to the FGPA. For example, the processor 10016 remote to the FGPA 10004 may aggregate data (e.g., multiple seconds of data). And the system may be able to display that aggregation of data. For example, it may be displayed as a graphic and/or metric 10026 representing a moving trend. This graphic and/or metric 10026 may be superimposed on the real-time data. Such trend information may be used to identify occlusions, instrument vascular sealing/clamping efficiency, vascular tree overviews, even oscillating magnitudes of motion over time. The FPGA 10004 may be configured to be on-the-fly updateable, for example, updatable with different (e.g., more sophisticated) transformations. These updates may come from local or remote communication servers. These updates may, for example, change the transform's analysis from refractivity (e.g., analysis of cellular irregularities), to blood flow, to multiple simultaneous depth analysis, and the like.

The FPGA updates may include transforms that implement a variety of imaging options for the user. These imaging options may include standard combined visual light, tissue refractivity, doppler shift, motion artifact correction, improved dynamic range, improved local clarity, super resolution, NIR florescence, multi-spectral imaging, confocal laser endomicroscopy, optical coherence tomography, raman spectroscopy, photoacoustic imaging, or any combination. The imaging options may include any of the options presented in any of the following: U.S. patent application Ser. No. 15/940,742, entitled “DUAL CMOS ARRAY IMAGING,” filed Mar. 29, 2018; U.S. patent application Ser. No. 13/952,564, entitled “WIDE DYNAMIC RANGE USING MONOCHROMATIC SENSOR,” FILED Jul. 26,2013; U.S. patent application Ser. No. 14/214,311, entitled “SUPER RESOLUTION AND COLOR MOTION ARTIFACT CORRECTION IN A PULSED COLOR IMAGING SYSTEM,” filed Mar. 14, 2014; U.S. patent application Ser. No. 13/952,550, entitled “CAMERA SYSTEM WITH MINIMAL AREA MONOLITIC CMOS IMAGE SENSOR,” filed Jul. 26, 2013, each of which is incorporated herein by reference in its entirety. Doppler wavelength shifting may be used to identify the number, size, speed, and/or directionality of moving particles, for example. Doppler wavelength shifting may be used with multiple laser wavelengths to interrelate the tissue depth and moving particles, for example. Tissue refractivity may be used for identification of irregular or variability of tissue superficial and sub-surface aspects, for example. In surgical practice, it may benefit identifying tumor margins, infection, broken surface tissue, adhesions, changes in tissue composition, and the like. NIR Fluorescence may include techniques in which systemically-injected drugs are preferentially absorbed by targeted tissue. When illuminated with the appropriate wavelength of light, they fluoresce and can be imaged through a NIR-capable scope/camera. Hyperspectral imaging and/or multispectral imaging may include the illumination and assessment of tissue across many wavelengths throughout the electromagnetic spectrum to provide real-time images. It may be used to differentiate between target tissues. It may also enable an imaging depth of 0-10 mm for example. Confocal laser endomicroscopy (CLE) may uses light to capture high-resolution, cellular level resolution without penetrating into tissue. It may provide a real-time histopathology of tissue. Technology that uses light to capture micrometer-resolution, 3D images from within tissues. Optical coherence tomography (OCT) may employ NIR light. OCT may enable imaging of tissue at depths of 1-2 mm, for example. Raman spectroscopy may include techniques that measure photon shifts caused by monochromatic laser illumination of tissue. It may be used to identify certain molecules. Photoacoustic imaging may include subjecting tissue to laser pulses such that a portion of the energy causes thermoelastic expansion and ultrasonic emission. These resulting ultrasonic waves may be detected and analyzed to form images.

These updates could be automatic based on user input or system compatibility checks. These real-time, aggregation, and updateable features of the system 10000 may be selectively enabled based on any aspect of the system's configuration, for example system capacity, power availability, free memory access, communication capacity, software level, tiered purchase levels, and/or the like.

The laser-light illumination source 10010 may include any illumination source of laser light suitable for analyzing human tissue. The laser-light illumination source 10010 may include a device such as the source laser emitters illustrated in FIGS. 17A-F, for example. The laser light illumination source 10010 may use one or more wavelengths of laser light to illuminate the tissue 10002. For example, the laser-light illumination source 10010 may use a red-blue-green-ultraviolet 1-ultraviolet 2-infrared combination. This combination with a 360-480 Hz sampling and actuation rate, for example, would allow for each light source to have multiple frames at an end user 60 Hz combined frame rate. A laser light wavelength combination with independent sources may increase resolution from a single array and may enable various depth penetration.

The tissue 10002 may be human tissue within a portion of a surgical field, for example. The laser light may reflect from the tissue 10002, resulting in reflected laser light. The reflected laser light may be received by the light sensor 10012. The light sensor 10012 may be configured to receive reflected laser light from a least a portion of the surgical field. The light sensor 10012 may be configured to receive laser light from the entirety of the surgical field. The light sensor may be configured to receive reflected laser light from a selectable portion of the surgical field. For example, a user, such as a surgeon, may direct the light sensor and the light laser light illumination source and/or the laser light illumination source to analyze specific portions of the surgical field.

The light sensor 10012 may be any device suitable for sensing reflected laser light and outputting corresponding information. For example, the light sensor 10012 may detect one or more characteristics of the reflected laser light, such as amplitude, frequency, wavelength, doppler shift, and/or other time domain or frequency domain qualities, for example. The laser-light sensor 10012 source may include a device such as the light sensor disclosed in connection with FIGS. 16A-D for example.

The laser-light sensor 10012 may include one or more sensor modules 10013. The sensor modules 10013 may be configured to measure a wide range of wavelengths. The sensor modules 10013 may be tuned and/or filtered to measure specific wavelengths for example. The sensor modules 10013 may include discrete sensors, a collection of sensors, a sensor array, a combination of sensor arrays, or the like, for example. For example, the sensor modules 10013 may include semiconductor components such as photodiodes, CMOS (complementary metal oxide semiconductor) image sensors, CCD (charge coupled device) image sensors, or the like.

The laser-light sensor 10012 may include a dual CMOS arrays. FIG. 31B shows an example laser-light sensor 10030. The laser-light sensor 10030 may include two sensor modules 10032, 10034. The sensor modules 10032, 10034 may be implemented as a dual side-by-side CMOS arrays. For example, the laser-light sensor 10030 be incorporated into the form factor of a surgical scope 10031 (e.g., a 7 mm diameter surgical scope) with two sensor modules 10032, 10034 (e.g., 2 side-by-side 4 mm sensors). The laser-light sensor 10030 may be configured to enable shifting between and/or among imaging modes. The modes may include three-dimensional stereoscopic and two-dimensional, simultaneous imaging (e.g., visual imaging together with imaging for refractivity analysis and/or Doppler analysis), for example. The modes may include imaging with a narrower or broader visualization range, for example. The modes may include imaging with lower or higher resolution and/or artifact correction, for example. The sensor modules 10032, 10034 may include different types of sensors. For example, a first sensor module 10032 may be a CMOS device. And the second sensor module 10034 may be a different CMOS device. The difference in CMOS devices may enable greater diversity of light collection capabilities. For example, different CMOS devices may enable broader light contrast and/or better light collection. For example, the first sensor array 10032 may have a higher quantity of pixel detectors relative to the second sensor array 10034. The surgical scope 10031 may include one or more light sources 10036, such as laser-light illumination sources for example.

FIG. 31C is a graphical representation of an example operation of a pixel array for a plurality of frames. Sensor modules (such as CMOS sensor modules, for example) may incorporate a pattern and/or technique for light sensing. The light sensing technique associated with operation of the sensor modules may incorporate filtering. The light sensing technique associated with the sensor modules may incorporate strobing of the light source. Examples of these techniques may include those disclosed herein in association with FIGS. 17C and 17D for example. A pattern of strobing light source may be used in connection with the sensor modules to measure the reflected light and to generate information indicative of the reflected light. Pixel arrays may be captured by rapidly strobing the visualized area at high speed with a variety of optical sources (either laser or light-emitting diodes) having different central optical wavelengths.

The strobing may cause the sensor to capture a respective pixel array associated with a corresponding wavelength. For example, in a first pattern 10038 red, green, and blue, and infrared (near-infrared for example) wavelength light may be strobed. Such a strobing may cause the sensor to capture a first pixel 10040 array of associated with the red wavelength, a second pixel array 10042 associated with the green wavelength, a third pixel array 10044 associated with the blue wavelength, a fourth pixel array 4046 associated with the green wavelength, a fifth pixel array 10048 associated with the infrared (near-infrared for example) wavelength, a sixth pixel array 10050 associated with the green wavelength, and a seventh pixel 10052 array associated with the blue wavelength, for example. For example, in a second pattern 1005 red, green, and blue, and infrared (near-infrared for example) wavelength light may be strobed. Such a strobing may cause the sensor to capture a eighth pixel 10056 array of associated with the red wavelength, a ninth pixel array 10058 associated with the green wavelength, a tenth pixel array 10060 associated with the blue wavelength, a eleventh pixel array 10062 associated with the green wavelength, a twelfth pixel array 10064 associated with the ultraviolet wavelength, a thirteenth pixel array 10066 associated with the green wavelength, and a fourteenth pixel array 10068 associated with the blue wavelength, for example.

Patterns, such as first pattern 10038 and second pattern 10054 for example, may be associated with one or more sensor modules. Patterns, such as first pattern 10038 and second pattern 10054 for example, may be associated with a mode of operation, as disclosed herein. Patterns, such as first pattern 10038 and second pattern 10054 for example, may be operated serially. Patterns, such as first pattern 10038 and second pattern 10054 for example, may be operated in parallel (with appropriate blanking for example). Patterns, such as first pattern 10038 and second pattern 10054 for example, may each be associated with a respective sensor module. Patterns, such as first pattern 10038 and second pattern 10054 for example, may be associated with sensor modules jointly.

As shown in FIG. 31A, the information collected by the light sensor 10012 may be communicated to the FPGA 10004. The FPGA 10004 may include any updatable gate array device suitable for analyzing data from a light sensor 10012. The FPGA 10004 may include one or more logic elements 10018. The logic elements 10018 may be configured to perform a transform on the incoming information. The FPGA 10004 may include an output suitable for passing analyzed and/or processed data representative of the tissue to the processor remote to the FPGA 10016 and/or the display 10014.

For example, the logic elements 10018 of the FPGA 10004 may provide information that may be passed to the display 10014 and displayed as a real-time data or a metric 10020 representative of a transform of reflected laser light information received by the light sensor 10012. The transform may include any mathematical and/or logical operation to transform data received from the light sensor 10012 to information indicative of partial motion. For example, the transform may include a Fast Fourier Transform (FFT).

The logic elements 10018 of the FGPA 10004 may provide a real-time data or metric 10020 to the display 10014 directly and/or in concert with the processor 10006 local to the field programmable gate array, for example. The real-time data and/or metric 10020 may include a representation of the motion of particles, such as particles per second for example. The real-time data and/or metric 10020 may be displayed on the display 10014. The real-time data and/or metric 10020 may be displayed as superimposed over a visualization of the tissue 10002.

For example, the logic elements 10018 of the FPGA 10004 may provide information that may be passed to the processor 10016 remote to the FPGA 10004 for aggregation and/or processing. The processor 10016 remote to the FPGA 10004 may provide an aggregation and analysis of this data. For example, the processor 10016 remote to the FPGA 10004 may provide running averages and other aggregation techniques. The processor 10016 remote to the FPGA 10004 may develop time aggregated data with variable time granularity. For example, the processor 10016 remote to the FPGA 10004 may aggregate several seconds of data from the field programmable gate array 10004. The processor 10016 remote to the FPGA 10004 may include other algorithms 10022 suitable for aggregating and analyzing data, such as least-squares regression techniques, polynomial fit techniques, other statistics such as average, mean, mode, max, min, variance and/or the like. The processor 10016 remote to the FPGA 10004 may include correlation algorithms correlating data received from the light sensor 10012 and/or data transformed by the FPGA 10004 with other aspects of the surgery, including for example, situational awareness data, procedure state, medical information, patient outcomes, other aggregated data such as adverse events like bleeding events. The processor 10016 remote to the FPGA 10004 may include certain artificial intelligence and/or machine learning-based algorithms. For example, previously acquired data may be used as a training set to one or more artificial intelligence and/or machine learning algorithms to provide further correlation between various surgical events and input received from the light sensor 10012 and input transformed by the FPGA 10004. Information resulting from an aggregation and analysis algorithm may be sent to the display 10014 (for example, sent in concert with the processor 10006 local to the FPGA 10004) for display to the user.

The display 10014 may include any device suitable for displaying information to a user. The display 10014 may include monitor 135 in connection with FIG. 3, for example. For example, display 10014 may include a traditional computer monitor. For example, the display 10014 may include any device suitable for displaying image and/or text data to a user. For example, the display 10014 may display image data 10024 received from the light sensor 10012 and/or other image sensors to depict a visual representation of the tissue 10002. The display 10014 may also be suitable for providing contextual information to the user including one or more displayed data elements. The data elements may include numerical or graphical representations of data and/or metrics. For example, the metrics may include one or more numbers accompanied by a graphical representation of the units. For example, the display 10014 may display a real-time metric 10020, such as the number of particles per second being detected according to the output of the FPGA 10004, for example. The display 10014 may display a processed metric 10026 (such as the rate of change of particles per second as determined over duration of time, for example) from an aggregation and analysis algorithm of the processor 10016 remote to the FPGA 10006.

The processor 10006 included local to the FPGA 10004 may include any device suitable for handling control processing of the surgical visualization system 10000. For example, the processor 10006 local to the FPGA may include a microprocessor, a microcontroller, a FPGA, and an application-specific integrated circuit (ASIC), a system-on-a-chip (SOIC), a digital signal processing (DSP) platform, a real-time computing system, or the like.

The processor 10006 local to the FPGA 10004 may provide control operation of any of the subcomponents of the surgical visualization system 10000. For example, the processor 10006 local to the FPGA 10004 may control operation of the laser light illumination source 10010. The processor 10006 local to the FPGA 10004 may provide timing for various laser light sequences, for example. The processor 10006 local to the FPGA 10004 may provide a modulation of frequency and/or amplitude of the laser light illumination source, for example. The processor 10006 local to the FPGA 10004 may direct the laser light illumination source to illuminate in any of the techniques disclosed in FIGS. 17A-F for example.

The processor 10006 local to the FPGA 10004 may be suitable for controlling operation of the light sensor 10012. For example, the processor 10006 local to the FPGA 10004 may direct the light sensor 10012 to provide certain sequences of shuttering such that certain light sensors are turned on or off at certain times for example. The processor 10006 local to the FPGA 10004 direct certain configurations of the light sensor 10012, such as local exposure, contrast, resolution, bandwidth, field-of-view, and imaging processing, for example.

The processor 10006 local to the FPGA 10004 may provide an internal networking function to direct dataflow between components of the surgical visualization system. For example, the processor 10006 local to the FPGA 10004 may direct data received from the light sensor 10012 to the FPGA 10004. The processor 10006 local to the FPGA 10004 may provide a switching fabric and/or direct a switching fabric to enable the appropriate communication of data from the light sensor 10012 to one or more logic elements 10018 of the FPGA 10004.

The processor 10006 local to the FPGA 10004 may control all or part of the operation of the display 10014. For example, the processor 10006 local to the FPGA 10004 may provide instructions for certain image data 10024, processed data and/or metrics 10026, and/or real-time data and/or metrics 10020 to be displayed on the display 10014.

The processor 10006 local to the FPGA 10004 may receive information from a user interface (not depicted in the figure). For example, processor 10006 local to the FPGA 10004 may receive certain selections of areas of interest on the image data 10024. To illustrate, if a surgeon were interested in the flow of particles in a specific area of the surgical field, the surgeon may select an area of interest on the display using a user interface (e.g., a keyboard and mouse) and processor 10006 local to the FPGA 10004 would respond accordingly. For example, by causing the surgical visualization system to determine and display one or more metrics associated with the selection made by the surgeon.

The processor 10006 local to the FPGA 10004 and/or the processor 10016 remote to the FPGA 10004 may operate either individually or in concert to enable configuration changes of the FPGA 10004. For example, the FPGA 10004 may include a first arrangement of logic elements to perform a first transform of the data. The FPGA 10004 may be configured to transition from the first arrangement of logic elements to a second arrangement of logic elements to perform a second transform of the data. For example, the processor 10006 local the FPGA 10004 and/or the processor 10016 remote to the FPGA 10004 may be suitable for adjusting, reconfiguring, and/or rearranging the arrangement or configuration of the logic elements 10018 of the FPGA 10004 such that the logic elements 10018 perform the second transform. The second transform may be different than the first transform. The second transform may be variant of the first transform. To illustrate this feature, an example first transform may include a 32-point Cooly-Tukey Radix-2 implemented Fast Fourier Transform (FFT) using an 11-bit signed integer input and the second transform may include a 1024-point Cooly-Tukey Radix-2 implemented FFT using a 12-bit signed integer input.

Data representative of various configurations of logic elements 10028 implementing different transforms may be available to the surgical visualization system. For example, the processor 10016 remote to the FPGA 10004 may have stored in a database one or more configuration configurations of logic elements 10028. These configurations 10028 may be updated from time to time. These configurations 10028 may represent various transforms. These configurations 10028 may represent transforms requiring different levels of hardware and processing resources. For example, they may include transforms that may be implemented by less sophisticated FPGAs and/or more sophisticated FPGAs. The configuration information 10028 may include configurations for transforms associated with various procedures and/or tissues. For example, the configuration information 10028 may include newly developed transforms and/or transforms developed in accordance with an analysis of the aggregated data over time. To illustrate this aspect and in one example, certain transforms may be determined to be better predictors of bleeding events in certain surgical procedures; such correlations may be used to further refine said transforms and then to promote the use of said transforms when similar patient data and/or procedural data dictates.

The upgradability of the transform may be associated with a purchased functional tier (e.g., a purchased software tier). For example, a purchased functional tier may enable the FGPA 10004 to be updatable and/or may make certain transforms available to the surgical visualization system 10000. The purchased functional tier be associated with a hospital, an operating room, a surgeon, a procedure, set of instrumentation, and/or a specific instrument, for example. To illustrate, a surgical visualization system 10000 may be installed at a hospital for use with a default transform. The default transform may include a generalized transform that is suitable for many procedures. Upon the purchase of an upgraded functional tier, the FPGA 10004 may be a reconfigured to implement an alternate transform, which may be more tailored for a specific procedure, tissue type, or surgeon's preference, for example.

Adaptive FPGA updates may enable variable overlays. Such overlays may include data and/or metrics from alternative sourced datasets. These datasets may be used to give context to the real-time particle movement and the aggregated trend data. For example, environment parameters may be controlled to affect blood flow and/or inflammation at a local surgical site. Monitoring the flow of fluids, the processor remote to the FPGA may recommend (or automatically alter, for example) room and/or patient settings. These setting changes may optimize the surgical location and/or improve device performance. For example, by monitoring the flow of blood, the user may receive visualization feedback to understand the outcome of an action (e.g., a staple and/or seal) prior to preforming. Settings such as an increase or decrease the body temperature, a raise/lower of bed angle, pressure and placement of compression cuffs, may be used, with visual feedback, to direct blood towards or away from a monitored location.

The memory 10008 may include any device suitable for storing and providing stored data. The memory may include read-only memory (ROM) and/or random-access memory (RAM). The memory 10008 may an include electrically erasable programmable read-only memory (EEPROM) for example. The memory 10008 may be suitable for an embedded system, for example. The memory 10008 be suitable for storing any intermediate data products in the operation of the surgical visualization system for example. The memory 10008 may be suitable for storing configuration information surgical visualization system, including one or more command parameters, and/or configuration information for the said logical elements. The memory 10008 may be suitable for storing system parameters. The memory 10008 may be suitable for providing one or more buffers, registers, and/or temporary storage of information.

FIG. 32 illustrates an example method for determining an operating mode. At 10200 real-time data may be collected. For example, a surgical visualization system may collect real-time data associated with a tissue. For example, a laser light illumination source may illuminate a tissue resulting in a reflected laser light which may be sensed by a light sensor and transformed according to a transform implemented in an arrangement of logical elements in a Field Programmable Gate Array (FPGA). This collection of real-time data may be presented to a user. This collection of real-time data may be processed and/or stored and/or aggregated by a processor local to the field programmable gate array and/or a processor remote to the field programmable gate array for example.

At 10202, a control parameter and/or input may be considered for logical processing. For example, this consideration of a control parameter and/or input may be used to determine whether operation is to continue in a default mode of operation and/or an alternate mode of operation. For example, there may be determination of system lockout status on local processing and trending based on system parameters.

An input from the user and/or control parameter the control parameter may include any number of parameters or any information suitable for helping determine whether to operate in operation in a default mode or an alternate mode. For example, data exchange with a locally located control system may be used as a control parameter. For example, a local control system in two-way communication with remote system may be used. For example, the control parameter may include any of band with processing capability memory capability. The control parameter may include a purchasing of a software tier. The input may include the input from a user such as a surgeon to select an alternate transform rather than the default transform. For example, the input may be a user input selecting a portion of the surgical field for specific analysis for example. The control parameter and/or input may include a control parameter and input suitable for indicating the enablement of an aggregation and/or analysis of aggregated data.

The determination of whether to operate in a default mode or an alternate mode may include displaying to user max capabilities of the data. The determination of whether to operate in a default mode or an alternate mode may include a notification and confirmation interaction with the user via a display and user interface. In accordance with the determination of whether to operate in a default mode or an alternate mode, operation may continue at 10204 in a default mode or at 10206 in an alternate mode. For example, operation in a default mode of operation may include the collection and processing of real-time data according to a default transform. And, operation in an alternate mode of operation may include operating in accordance with a transform or a second transform or an alternate transform for the collection of real-time data for example.

In a surgical visualization system with light generation and an imaging sensor array, transform of detected light may transform that information into moving particle size, rate, and volume. The result of the transform may be displayed on a monitor. The default transform and/or the alternate transform may include various program parameters. Output from the default transform and/or the alternate transform may be coupled to exterior processing to determine trending and aggregation of data. Whether to operate in the default mode of operation and the alternate mode of operation may include a choice to display particle data, trending data, layered data, etc. The choice may be dependent on a system control parameter.

FIG. 33 illustrates an example method for displaying real-time and trending information to a user. The real-time transformations of the Doppler shift of a light wavelength may be exported to a processor component. The processor component may be capable of storing an amount of previous seconds of datasets. These datasets may be used as a reference to aggregate motion data into trending data. And, the trending data may be superimposed on a display to show both real-time movement and moving trends.

The moving trends may be compared with historic data (e.g., local historic data from previous minutes and/or hours within the same procedure, longer-term historic data), for example. The moving trends may be compared with data from local and/or external sources, for example. Comparisons may provide context of the trending, for example trending relative to a baseline. For example, comparisons may be made from the same patient at a different time. For example, comparisons may be made from one or more similar patients (e.g., patients with similar relevant traits). Comparisons may be used to in form surgeon decisions.

At 10300, real-time data may be collected. Laser light may be shown onto tissue in a surgical field and reflected back towards a light sensor. The real-time data may include data received by the light sensor. The real-time data may include a representation of the frequency and/or wavelength of the reflected light.

Moving particles in the surgical field may cause a Doppler shift in the wavelength of the reflected light. At 10302, the real-time data may be transformed by a transform to assess the Doppler shift. The resulting information may represent an aspect of the moving particles, such as speed, velocity, volume, for example. This resulting information may be displayed to a user, at 10304.

In addition, the max capabilities of the data and/or system may be displayed to the user. And, at 10306, the resulting information and/or the real-time data may be aggregated and/or further analyzed. For example, it may be processed with the situational awareness. For example, this may enable the separation and/or identification of blood flow, interstitial fluids, smoke, particulates, mist, aerosols and/or the like. And it may enable display of selected data without noise from other data types. For example, user selection of highlighted particle tracking may engage further processing and analysis to focus the display to the desired real-time data, resulting information, etc. For example, the user may select a type of data to be displayed, such as size of particles, volume, rate of increase, velocity of particle groups, and/or movement over time of a tagged group, etc. The resulting information and/or the real-time data may be aggregated and/or further analyzed to determine, for example, trends over time, transformations to time rate of change aspects (e.g., acceleration, etc.), calibrations and/or adjustments for temperature, insufflation gas types, laser source, combined laser data set, and the like. The aggregation and analysis may occur concurrently with displaying the real-time information. The aggregation and analysis of information on moving particles may occur at some time after displaying the real-time data on moving particles. The aggregation and analysis information on moving particles may occur without the display of real-time information on moving particles. The aggregation and analysis of information on moving particles may include any number of algorithms and our analysis suitable for analyzing visualization data.

At 10308, the information resulting from the aggregation and further analysis (e.g., trending information) may be displayed to the user. The trending information may be combined into graphical trend animations. The trending information may be shown as a metric. The trending information may be superimposed on the raw moving particle data.

FIG. 34 depicts an example user interface with real-time and/or trending information being displayed. A first user interface 10402 includes image data. This image data may represent an image portion 2810 of a surgical field. The image portion 2810 may present a close-up view of the vascular tree 2814 so that the surgeon can focus on dissecting only the blood vessel of interest 2815. For resecting the blood vessel of interest 2815, a surgeon may use a smart RF cautery device 2816. The image data may be developed by way of a CMOS image sensor and/or a light sensor. Data may also be collected by wideband light and/or laser light impinged on this tissue, being received by a light sensor, and being processed in real-time by way of a transform. The output of this transform may be a metric 10404 and/or other representation of the number of particles per second of motion within a certain portion of the field-of-view. For example, this metric may represent particles of smoke, liquid, blood cells, or the like for example. The metric 10404 may be displayed on the first user interface 10402.

A user interface element 10405 may be displayed to the user. For example, the user interface element 10405 may include a text box indicating whether or not the surgeon would like to engage local and/or remote processing for further analysis of the data. Certain conditions may be required to be satisfied to engage such processing. For example, engagement may be conditioned on the purchase of a software tier. For example, engagement may be conditioned on bandwidth and/or processing capabilities.

In view of the engagement, trend information 10406 may be displayed on second user interface 10408. The second user interface 10408 may be displayed on a display. For example, the trend data may include a metric of particles per second squared and/or an info graphic or other visualization, such as a chart, icon, graph or the like.

The real-time metric 10404, such as particles per second for example, and the trend information 10406, such as particle acceleration for example, may be included on the second user interface. These information elements may be displayed to the user. For example, real-time metric 10404 and the trend information 10406 they may be superimposed over the image data. Such real-time metric 10404, such as particles per second for example, and/or the trend information 10406, such as particle acceleration for example, may be useful to a surgeon performing a resection of the blood vessel 2815.

FIG. 35 depicts an example upgrade framework for a surgical visualization system. The framework includes a two-by-two. The left axis represents inputs. The bottom access represents transforms and/or algorithms. When performing an update to a surgical visualization system, the update may include a change to the inputs, such as changing the wavelength, pattern, intensity of light for example. The change to the inputs may include a change from a single wavelength to a multispectral input for example. When performing an update to a surgical visualization system, the update may include a change to the transforms and/or algorithms. The transform may include a new adjusting the transform for processing efficiency, responsiveness, energy usage, bandwidth, or the like.

As illustrated, an update may take the form of any box within the grid. An update may include a change of the inputs with the transform and/or algorithm remaining the same. An update may include a change of the transform and/or algorithm with the inputs being the same. An update may include a change of the transform and/or algorithm and a change to the inputs.

FIG. 36 illustrates an example method for reconfiguring a FPGA. At 10602 a predefined FPGA transform may be used to transform multispectral imaging data. At 10604, information generated from this transform may be subject to aggregation and/or further analysis. The aggregation and further analysis may identify an alternative transform that is more suitable for a particular purpose. The system may request and/or receive input (such as a control parameter, for example) associated with an update to the transform, at 10606. If such an input and/or control parameter is indicative of not updating, the system may continue with existing transform, at 10608. If the system is upgradable, the system may obtain an alternate configuration, at 10610. The logic elements in the FPGA may be reconfigured in accordance with the alternate configuration to reflect the updated transform, at 10612. The system may resume multispectral imaging with the updated FPGA transform. 

1. A surgical visualization system to analyze at least a portion of a surgical field, the system comprising: a laser-light illumination source configured to illuminate the at least a portion of the surgical field with laser-light; a light sensor configured to receive reflected laser-light; a field programable gate array configured to transform information indicative of the reflected laser-light to information indicative of moving particles in the at least a portion of the surgical field; a display configured to display an image comprising the at least the portion of the surgical field, and a processor configured to control the display to display a first metric and a second metric superimposed on the image, wherein the first metric represents a present state of moving particles in the at least a portion of the surgical field, and wherein the second metric represents an aggregated state of moving particles in the at least a portion of the surgical field.
 2. The surgical visualization system of claim 1, wherein the aggregated state of moving particles in the at least a portion of the surgical field comprises a data trend.
 3. The surgical visualization system of claim 1, wherein the second metric represents an aggregation of several seconds and is shown as a trend.
 4. The surgical visualization system of claim 1, wherein the second metric is suitable to identify any of occlusions, instrument vascular sealing/clamping efficiency, vascular tree overviews, and oscillating magnitudes of motion over time.
 5. The surgical visualization system of claim 1, wherein the second metric comprises an acceleration of moving particles in the at least the portion of the surgical field.
 6. The surgical visualization system of claim 1, wherein the the processor is configured to control the display to display a graphical trend animation superimposed on the image.
 7. The surgical visualization system of claim 1, further comprising a user interface to receive a user selection of the type of unit to be used to display the second metric.
 8. The surgical visualization system of claim 1, further comprising a user interface to receive a user selection of a tagged group of particles, wherein the second metric represents the aggregated state of the tagged group of particles.
 9. The surgical visualization system of claim 1, wherein the processors comprises a first processor associated with an image acquisition module, and wherein the system further comprises a second processor associated with an external processing resource, wherein the information indicative of moving particles in the at least a portion of the surgical field is communicated to the second processor for aggregation analysis, and wherein information indicative of the second metric is communicated from the second processor to the first processor.
 10. A surgical visualization system to analyze at least a portion of a surgical field, the system comprising: a field programable gate array configured to transform information indicative of reflected laser-light to information indicative of moving particles in the at least a portion of the surgical field; a first processor, co-housed with the field programable gate array, configured to generate a first metric that represents a present state of moving particles in the at least a portion of the surgical field; and a second processor, remote to the field programmable gate array, configured to receive the information indicative of moving particles in the at least a portion of the surgical field and to generate a second metric that represents an aggregated state of moving particles in the at least a portion of the surgical field.
 11. The surgical visualization system of claim 10, further comprising a display, wherein the second processor communicates the second metric to the first processor, and wherein the first processor directs the display to display the first metric and the second metric superimposed over an image comprising the at least a portion of the surgical field.
 12. The surgical visualization system of claim 10, further comprising a laser-light illumination source configured to illuminate the at least a portion of the surgical field with laser-light and a light sensor configured to the receive reflected laser-light.
 13. The surgical visualization system of claim 10, wherein the aggregated state of moving particles in the at least a portion of the surgical field comprises a data trend.
 14. The surgical visualization system of claim 10, wherein the second metric represents an aggregation of several seconds and is shown as a trend.
 15. The surgical visualization system of claim 10, wherein the second metric is suitable to identify any of occlusions, instrument vascular sealing/clamping efficiency, vascular tree overviews, and oscillating magnitudes of motion over time.
 16. The surgical visualization system of claim 10, wherein the second metric comprises an acceleration of moving particles in the at least the portion of the surgical field.
 17. A surgical visualization system to analyze at least a portion of a surgical field, the system comprising: a display configured to display an image comprising the at least the portion of the surgical field, and a processor configured to control the display to display a first metric and a second metric superimposed on the image, wherein the first metric represents a present state of moving particles in the at least a portion of the surgical field, and wherein the second metric represents an aggregated state of moving particles in the at least a portion of the surgical field.
 18. The surgical visualization system of claim 17, wherein the aggregated state of moving particles in the at least a portion of the surgical field comprises a data trend.
 19. The surgical visualization system of claim 17, wherein the second metric represents an aggregation of several seconds and is shown as a trend.
 20. The surgical visualization system of claim 17, further comprising a user interface to receive a user selection of a tagged group of particles, wherein the second metric represents the aggregated state of the tagged group of particles. 